bluuebunny/crossref_metadata_2025 huggingface dataset:
Drug-Like Small Molecule HSP27 Functional Inhibitor Sensitizes Lung Cancer Cells to Gefitinib or Cisplatin by Inducing Altered Cross-Linked Hsp27 Dimers
Authors: Yoo Hawon , Choi Seul-Ki , Lee Jaeok , Park So Hyeon , Park You Na , Hwang Soo-Yeon , Shin Jae-Ho , Na Younghwa , Kwon Youngjoo , Lee Hwa Jeong , Lee Yun-Sil
Published: April 2021

Relationships between heat shock protein 27 (HSP27) and cancer aggressiveness, metastasis, drug resistance, and poor patient outcomes in various cancer types including non-small cell lung cancer (NSCLC) were reported, and inhibition of HSP27 expression is suggested to be a possible strategy for cancer therapy. Unlike HSP90 or HSP70, HSP27 does not have an ATP-binding pocket, and no effective HSP27 inhibitors have been identified. Previously, NSCLC cancer cells were sensitized to radiation and chemotherapy when co-treated with small molecule HSP27 functional inhibitors such as zerumbone (ZER), SW15, and J2 that can induce abnormal cross-linked HSP27 dimer. In this study, cancer inhibition effects of NA49, a chromenone compound with better solubility, longer circulation time, and less toxicity than J2, were examined in combination with anticancer drugs such as cisplatin and gefitinib in NSCLC cell lines. When the cytotoxic drug cisplatin was treated in combination with NA49 in epidermal growth factor receptors (EGFRs) WT cell lines, sensitization was induced in an HSP27 expression-dependent manner. With gefitinib treatment, NA49 showed increased combination effects in both EGFR WT and Mut cell lines, also with HSP27 expression-dependent patterns. Moreover, NA49 induced sensitization in EGFR Mut cells with a secondary mutation of T790M when combined with gefitinib. Augmented tumor growth inhibition was shown with the combination of cisplatin or gefitinib and NA49 in nude mouse xenograft models. These results suggest the combination of HSP27 inhibitor NA49 and anticancer agents as a candidate for overcoming HSP27-mediated drug resistance in NSCLC patients.
Polymeric Carriers Designed for Encapsulation of Essential Oils with Biological Activity
Authors: Chiriac Aurica P. , Rusu Alina G. , Nita Loredana E. , Chiriac Vlad M. , Neamtu Iordana , Sandu Alina
Published: April 2021

The article reviews the possibilities of encapsulating essential oils EOs, due to their multiple benefits, controlled release, and in order to protect them from environmental conditions. Thus, we present the natural polymers and the synthetic macromolecular chains that are commonly used as networks for embedding EOs, owing to their biodegradability and biocompatibility, interdependent encapsulation methods, and potential applicability of bioactive blend structures. The possibilities of using artificial intelligence to evaluate the bioactivity of EOs—in direct correlation with their chemical constitutions and structures, in order to avoid complex laboratory analyses, to save money and time, and to enhance the final consistency of the products—are also presented.
Antifungal Activity of Novel Formulations Based on Terpenoid Prodrugs against C. albicans in a Mouse Model
Authors: Menon Suvidha , Liang Xiuyi , Vartak Richa , Patel Ketankumar , Di Stefano Antonio , Cacciatore Ivana , Marinelli Lisa , Billack Blase
Published: April 2021

Carvacrol (CAR), a phenolic monoterpenoid, has been extensively investigated for its antimicrobial and antifungal activity. As a result of its poor physicochemical properties, water soluble carvacrol prodrugs (WSCPs) with improved water solubility were previously synthesized and found to possess antimicrobial activity. Here, three novel CAR analogs, WSCP1, WSCP2, and WSCP3, were tested against fluconazole (FLU)-sensitive and -resistant strains where they showed greater antifungal activity than CAR against C. albicans. The probable mechanism by which the CAR prodrugs exert the antifungal activity was studied. Results from medium acidification assays demonstrated that the CAR and its synthetically designed prodrugs inhibit the yeast plasma membrane H+-ATPase (Pma1p), an essential target in fungi. In other words, in vitro data indicated that CAR analogs can prove to be a better alternative to CAR considering their improved water solubility. In addition, CAR and WSCP1 were developed into intravaginal formulations and administered at test doses of 50 mg/kg in a mouse model of vulvovaginal candidiasis (VVC). Whereas the CAR and WSCP1 formulations both exhibited antifungal efficacy in the mouse model of VVC, the WSCP1 formulation was superior to CAR, showing a remarkable decrease in infection by ~120-fold compared to the control (infected, untreated animals). Taken together, a synthetically designed prodrug of CAR, namely WSCP1, proved to be a possible solution for poorly water-soluble drugs, an inhibitor of an essential yeast pump in vitro and an effective and promising antifungal agent in vivo.
Linear Combinations of the Complex Degrees of Coherence
Authors: Mei Zhangrong , Korotkova Olga
Published: April 2021

We propose a method for structuring the spatial coherence state of light via mixed linear combinations of N complex degrees of coherence (CDC) and specify the conditions under which such combinations represent a valid CDC. Several examples demonstrate that this method opens previously unknown avenues for modeling random sources, radiating to light fields with unique features.
Genome-Wide Identification and Development of LTR Retrotransposon-Based Molecular Markers for the Melilotus Genus
Authors: Ouyang Zifeng , Wang Yimeng , Ma Tiantian , Kanzana Gisele , Wu Fan , Zhang Jiyu
Published: April 2021

Melilotus is an important genus of legumes with industrial and medicinal value, partly due to the production of coumarin. To explore the genetic diversity and population structure of Melilotus, 40 accessions were analyzed using long terminal repeat (LTR) retrotransposon-based markers. A total of 585,894,349 bp of LTR retrotransposon sequences, accounting for 55.28% of the Melilotus genome, were identified using bioinformatics tools. A total of 181,040 LTR retrotransposons were identified and classified as Gypsy, Copia, or another type. A total of 350 pairs of primers were designed for assessing polymorphisms in 15 Melilotus albus accessions. Overall, 47 polymorphic primer pairs were screened for their availability and transferability in 18 Melilotus species. All the primer pairs were transferable, and 292 alleles were detected at 47 LTR retrotransposon loci. The average polymorphism information content (PIC) value was 0.66, which indicated that these markers were highly informative. Based on unweighted pair group method with arithmetic mean (UPGMA) dendrogram cluster analysis, the 18 Melilotus species were classified into three clusters. This study provides important data for future breeding programs and for implementing genetic improvements in the Melilotus genus.
Sesquiterpene Lactones from Artemisia absinthium. Biotransformation and Rearrangement of the Insect Antifeedant 3α-hydroxypelenolide
Authors: Fraga Braulio M. , Díaz Carmen E. , Bailén María , González-Coloma Azucena
Published: April 2021

Three new compounds, the sesquiterpenes absilactone and hansonlactone and the acetophenone derivative ajenjol, have been isolated from a cultivated variety of Artemisia absinthium. In addition, the major lactone isolated, 3α-hydroxypelenolide, was biotransformed by the fungus Mucor plumbeus affording the corresponding 1β, 10α-epoxide. A cadinane derivative was formed by an acid rearrangement produced in the culture medium, but not by the enzymatic system of the fungus. Furthermore, 3α-hydroxypelenolide showed strong antifeedant effects against Leptinotarsa decemlineata and cytotoxic activity to Sf9 insect cells, while the biotransformed compounds showed antifeedant postingestive effects against Spodoptera littoralis.
Detection of Reproducible Major Effect QTL for Petal Traits in Garden Roses
Authors: Schulz Dietmar , Linde Marcus , Debener Thomas
Published: April 2021

The detection of QTL by association genetics depends on the genetic architecture of the trait under study, the size and structure of the investigated population and the availability of phenotypic and marker data of sufficient quality and quantity. In roses, we previously demonstrated that major QTL could already be detected in small association panels. In this study, we analyzed petal number, petal size and fragrance in a small panel of 95 mostly tetraploid garden rose genotypes. After genotyping the panel with the 68 K Axiom WagRhSNP chip we detected major QTL for all three traits. Each trait was significantly influenced by several genomic regions. Some of the QTL span genomic regions that comprise several candidate genes. Selected markers from some of these regions were converted into KASP markers and were validated in independent populations of up to 282 garden rose genotypes. These markers demonstrate the robustness of the detected effects independent of the set of genotypes analyzed. Furthermore, the markers can serve as tools for marker-assisted breeding in garden roses. Over an extended timeframe, they may be used as a starting point for the isolation of the genes underlying the QTL.
Characterizing Bacterial Cellulose Produced byKomagataeibacter sucrofermentans H-110 on Molasses Medium and Obtaining a Biocomposite Based on It for the Adsorption of Fluoride
Authors: Revin Viktor V. , Dolganov Alexander V. , Liyaskina Elena V. , Nazarova Natalia B. , Balandina Anastasia V. , Devyataeva Anna A. , Revin Vadim D.
Published: April 2021

Currently, there is an increased demand for biodegradable materials in society due to growing environmental problems. Special attention is paid to bacterial cellulose, which, due to its unique properties, has great prospects for obtaining functional materials for a wide range of applications, including adsorbents. In this regard, the aim of this study was to obtain a biocomposite material with adsorption properties in relation to fluoride ions based on bacterial cellulose using a highly productive strain of Komagataeibacter sucrofermentans H-110 on molasses medium. Films of bacterial cellulose were obtained. Their structure and properties were investigated by FTIR spectroscopy, NMR, atomic force microscopy, scanning electron microscopy, and X-ray structural analysis. The results show that the fiber thickness of the bacterial cellulose formed by the K. sucrofermentans H-110 strain on molasses medium was 60–90 nm. The degree of crystallinity of bacterial cellulose formed on the medium was higher than on standard Hestrin and Schramm medium and amounted to 83.02%. A new biocomposite material was obtained based on bacterial cellulose chemically immobilized on its surface using atomic-layer deposition of nanosized aluminum oxide films. The composite material has high sorption ability to remove fluoride ions from an aqueous medium. The maximum adsorption capacity of the composite is 80.1 mg/g (F/composite). The obtained composite material has the highest adsorption capacity of fluoride from water in comparison with other sorbents. The results prove the potential of bacterial cellulose-based biocomposites as highly effective sorbents for fluoride.
Fabrication and Thermo-Electro and Mechanical Properties Evaluation of Helical Multiwall Carbon Nanotube-Carbon Fiber/Epoxy Composite Laminates
Authors: Ali Alamry , Andriyana Andri , Hassan Shukur Bin Abu , Ang Bee Chin
Published: April 2021

The development of advanced composite materials has taken center stage because of its advantages over traditional materials. Recently, carbon-based advanced additives have shown promising results in the development of advanced polymer composites. The inter- and intra-laminar fracture toughness in modes I and II, along with the thermal and electrical conductivities, were investigated. The HMWCNTs/epoxy composite was prepared using a multi-dispersion method, followed by uniform coating at the mid-layers of the CF/E prepregs interface using the spray coating technique. Analysis methods, such as double cantilever beam (DCB) and end notched flexure (ENF) tests, were carried out to study the mode I and II fracture toughness. The surface morphology of the composite was analyzed using field emission scanning electron microscopy (FESEM). The DCB test showed that the fracture toughness of the 0.2 wt.% and 0.4 wt.% HMWCNT composite laminates was improved by 39.15% and 115.05%, respectively, compared with the control sample. Furthermore, the ENF test showed that the mode II interlaminar fracture toughness for the composite laminate increased by 50.88% and 190%, respectively. The FESEM morphology results confirmed the HMWCNTs bridging at the fracture zones of the CF/E composite and the improved interlaminar fracture toughness. The thermogravimetric analysis (TGA) results demonstrated a strong intermolecular bonding between the epoxy and HMWCNTs, resulting in an improved thermal stability. Moreover, the differential scanning calorimetry (DSC) results confirmed that the addition of HMWCNT shifted the Tg to a higher temperature. An electrical conductivity study demonstrated that a higher CNT concentration in the composite laminate resulted in a higher conductivity improvement. This study confirmed that the demonstrated dispersion technique could create composite laminates with a strong interfacial bond interaction between the epoxy and HMWCNT, and thus improve their properties.
Chemical Imaging of Single Anisotropic Polystyrene/Poly (Methacrylate) Microspheres with Complex Hierarchical Architecture
Authors: Wagner Alexandra , Wagner Stefanie , Bredfeldt Jan-Erik , Steinbach Julia C. , Mukherjee Ashutosh , Kronenberger Sandra , Braun Kai , Kandelbauer Andreas , Mayer Hermann A. , Brecht Marc
Published: April 2021

Monodisperse polystyrene spheres are functional materials with interesting properties, such as high cohesion strength, strong adsorptivity, and surface reactivity. They have shown a high application value in biomedicine, information engineering, chromatographic fillers, supercapacitor electrode materials, and other fields. To fully understand and tailor particle synthesis, the methods for characterization of their complex 3D morphological features need to be further explored. Here we present a chemical imaging study based on three-dimensional confocal Raman microscopy (3D-CRM), scanning electron microscopy (SEM), focused ion beam (FIB), diffuse reflectance infrared Fourier transform (DRIFT), and nuclear magnetic resonance (NMR) spectroscopy for individual porous swollen polystyrene/poly (glycidyl methacrylate-co-ethylene di-methacrylate) particles. Polystyrene particles were synthesized with different co-existing chemical entities, which could be identified and assigned to distinct regions of the same particle. The porosity was studied by a combination of SEM and FIB. Images of milled particles indicated a comparable porosity on the surface and in the bulk. The combination of standard analytical techniques such as DRIFT and NMR spectroscopies yielded new insights into the inner structure and chemical composition of these particles. This knowledge supports the further development of particle synthesis and the design of new strategies to prepare particles with complex hierarchical architectures.
Magnetic Metal Organic Framework Immobilized Laccase for Wastewater Decolorization
Authors: Amari Abdelfattah , Alzahrani Fatimah Mohammed , Alsaiari Norah Salem , Katubi Khadijah Mohammedsaleh , Rebah Faouzi Ben , Tahoon Mohamed A.
Published: April 2021

The laccase enzyme was successfully immobilized over a magnetic amino-functionalized metal–organic framework Fe3O4-NH2@MIL-101(Cr). Different techniques were used for the characterization of the synthesized materials. The Fe3O4-NH2@MIL-101(Cr) laccase showed excellent resistance to high temperatures and low pH levels with a high immobilization capacity and large activity recovery, due to the combination of covalent binding and adsorption advantages. The long-term storage of immobilized laccase for 28 days indicated a retention of 88% of its initial activity, due to the high stability of the immobilized system. Furthermore, a residual activity of 49% was observed at 85 °C. The immobilized laccase was effectively used for the biodegradation of Reactive Black 5 (RB) and Alizarin Red S (AR) dyes in water. The factors affecting the RB and AR degradation using the immobilized laccase (dye concentration, temperature and pH) were investigated to determine the optimum treatment conditions. The optimum conditions for dye removal were a 5 mg/L dye concentration, temperature of 25 °C, and a pH of 4. At the optimum conditions, the biodegradation and sorption-synergistic mechanism of the Fe3O4-NH2@MIL-101(Cr) laccase system caused the total removal of AR and 81% of the RB. Interestingly, the reusability study of this immobilized enzyme up to five cycles indicated the ability to reuse it several times for water treatment.
A Transcript of Submission: Jesus as Fated Victim of Divine Violence in the Old Saxon Heliand
Authors: Youngs Samuel J.
Published: April 2021

The Heliand, written shortly after the conquest and conversion of the Saxons at the hands of Charlemagne, maintains a vexed place in the study of medieval European Christianity(ies). Some argue that the Heliand’s overarching intent was pastoral, meant to ease the fears and calm the rage of the defeated Saxons, while others posit that the Heliand reflects a “dissident gospel,” aimed at subverting the official theological outlook of the Carolingian empire. This study argues that while both theories capture something of the Heliand’s ingenious contextual impact, they underestimate one of its key themes: the role of wurd (fate) and its co-identification with the “power of God,” which drives Jesus to the cross and scaffolds his submission to the violence of the divine will. Thus, the Heliand presents compliant victimization as the proper “fate” of those who submit to God’s purposes, promising a heavenly reward and countermanding the Saxon ethos of resistance.
Introduction to the Special Issue “Religious and Spiritual Experiences”
Authors: Austad Anne , Muthert Hanneke
Published: April 2021

William James’s seminal book, The Varieties of Religious Experience (1902/2012), describes the phenomenology and ‘fruits’ (James 2012, p [...]
Professionalizing the Imam in Europe: Imam Training Programs as Sites of Deliberative Engagement
Authors: Boender Welmoet
Published: April 2021

This article discusses the first experiences of a supplementary imam training program that has been designed in the Netherlands for community-based imams, female religious leaders and mosque committee members. This “Professionalization of Imams in the Netherlands” program (PIN) was set up as a cooperation of the Representative Council of Muslims (CMO) and Vrije Universiteit Amsterdam, supported by state-subsidy. The article discusses how the initiators maneuvered within and beyond the politicized burden of expectation that has surrounded the establishment of European-based imam training programs for decades now. The article provides a unique insight into the program’s design, its collaborative partners and participants’ experiences, understanding the program as a site of deliberative engagement. It shows how the stakeholders ideally see ownership of the curriculum and trainee recruitment as a shared responsibility for the Muslim community and the public educational institution, whereas the state is willing to finance it. The article outlines how in this attempt the stakeholders must deal with some paradoxical dynamics that influence this notion of “shared ownership”. Sharing these analytical observations and recommendations will hopefully help stakeholders involved in setting up similar European programs to make rational decisions on content and format of (future) supplementary programs, within and beyond fields of power, authority and interest.
The Problem of Evil, Skeptical Theism and Moral Epistemology
Authors: Coley Scott M.
Published: April 2021

This paper argues that skeptical theism isn’t susceptible to criticisms of the view presented in James Sterba’s new book on the logical problem of evil. Nevertheless, Sterba’s argument does serve to underscore the unpalatable moral-epistemological consequences of skeptical theistic skepticism (STS): for precisely the reasons that STS doesn’t succumb to Sterba’s critique, STS threatens to undermine moral knowledge altogether.
Medieval Monastery Gardens in Iceland and Norway
Authors: Åsen Per Arvid
Published: April 2021

Gardening was an important part of the daily duties within several of the religious orders in Europe during the Middle Ages. The rule of Saint Benedict specified that the monastery should, if possible, contain a garden within itself, and before and above all things, special care should be taken of the sick, so that they may be served in very deed, as Christ himself. The cultivation of medicinal and utility plants was important to meet the material needs of the monastic institutions, but no physical garden has yet been found and excavated in either Scandinavia or Iceland. The Cistercians were particularly well known for being pioneer gardeners, but other orders like the Benedictines and Augustinians also practised gardening. The monasteries and nunneries operating in Iceland during medieval times are assumed to have belonged to either the Augustinian or the Benedictine orders. In Norway, some of the orders were the Dominicans, Fransiscans, Premonstratensians and Knights Hospitallers. Based on botanical investigations at all the Icelandic and Norwegian monastery sites, it is concluded that many of the plants found may have a medieval past as medicinal and utility plants and, with all the evidence combined, they were most probably cultivated in monastery gardens.
The Passive Microwave Neural Network Precipitation Retrieval Algorithm for Climate Applications (PNPR-CLIM): Design and Verification
Authors: Bagaglini Leonardo , Sanò Paolo , Casella Daniele , Cattani Elsa , Panegrossi Giulia
Published: April 2021

This paper describes the Passive microwave Neural network Precipitation Retrieval algorithm for climate applications (PNPR-CLIM), developed with funding from the Copernicus Climate Change Service (C3S), implemented by ECMWF on behalf of the European Union. The algorithm has been designed and developed to exploit the two cross-track scanning microwave radiometers, AMSU-B and MHS, towards the creation of a long-term (2000–2017) global precipitation climate data record (CDR) for the ECMWF Climate Data Store (CDS). The algorithm has been trained on an observational dataset built from one year of MHS and GPM-CO Dual-frequency Precipitation Radar (DPR) coincident observations. The dataset includes the Fundamental Climate Data Record (FCDR) of AMSU-B and MHS brightness temperatures, provided by the Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO) project, and the DPR-based surface precipitation rate estimates used as reference. The combined use of high quality, calibrated and harmonized long-term input data (provided by the FIDUCEO microwave brightness temperature Fundamental Climate Data Record) with the exploitation of the potential of neural networks (ability to learn and generalize) has made it possible to limit the use of ancillary model-derived environmental variables, thus reducing the model uncertainties’ influence on the PNPR-CLIM, which could compromise the accuracy of the estimates. The PNPR-CLIM estimated precipitation distribution is in good agreement with independent DPR-based estimates. A multiscale assessment of the algorithm’s performance is presented against high quality regional ground-based radar products and global precipitation datasets. The regional and global three-year (2015–2017) verification analysis shows that, despite the simplicity of the algorithm in terms of input variables and processing performance, the quality of PNPR-CLIM outperforms NASA GPROF in terms of rainfall detection, while in terms of rainfall quantification they are comparable. The global analysis evidences weaknesses at higher latitudes and in the winter at mid latitudes, mainly linked to the poorer quality of the precipitation retrieval in cold/dry conditions.
Emerging Pattern of Wind Change over the Eurasian Marginal Seas Revealed by Three Decades of Satellite Ocean-Surface Wind Observations
Authors: Yu Lisan
Published: April 2021

This study provides the first full characterization of decadal changes of surface winds over 10 marginal seas along the Eurasian continent using satellite wind observations. During the three decades (1988–2018), surface warming has occurred in all seas at a rate more pronounced in the South European marginal seas (0.4–0.6 °C per decade) than in the monsoon-influenced North Indian and East Asian marginal seas (0.1–0.2 °C per decade). However, surface winds have not strengthened everywhere. On a basin average, winds have increased over the marginal seas in the subtropical/mid-latitudes, with the rate of increase ranging from 11 to 24 cms−1 per decade. These upward trends reflect primarily the accelerated changes in the 1990s and have largely flattened since 2000. Winds have slightly weakened or remained little changed over the marginal seas in the tropical monsoonal region. Winds over the Red Sea and the Persian Gulf underwent an abrupt shift in the late 1990s that resulted in an elevation of local wind speeds. The varying relationships between wind and SST changes suggest that different marginal seas have responded differently to environmental warming and further studies are needed to gain an improved understanding of climate change on a regional scale.
Modeling and Classification of Alluvial Fans with DEMs and Machine Learning Methods: A Case Study of Slovenian Torrential Fans
Authors: Babič Matej , Petrovič Dušan , Sodnik Jošt , Soldo Božo , Komac Marko , Chernieva Olena , Kovačič Miha , Mikoš Matjaž , Calì Michele
Published: April 2021

Alluvial (torrential) fans, especially those created from debris-flow activity, often endanger built environments and human life. It is well known that these kinds of territories where human activities are favored are characterized by increasing instability and related hydrological risk; therefore, treating the problem of its assessment and management is becoming strongly relevant. The aim of this study was to analyze and model the geomorphological aspects and the physical processes of alluvial fans in relation to the environmental characteristics of the territory for classification and prediction purposes. The main geomorphometric parameters capable of describing complex properties, such as relative fan position depending on the neighborhood, which can affect their formation or shape, or properties delineating specific parts of fans, were identified and evaluated through digital elevation model (DEM) data. Five machine learning (ML) methods, including a hybrid Euler graph ML method, were compared to analyze the geomorphometric parameters and physical characteristics of alluvial fans. The results obtained in 14 case studies of Slovenian torrential fans, validated with data of the empirical model proposed by Bertrand et al. (2013), confirm the validity of the developed method and the possibility to identify alluvial fans that can be considered as debris-flow prone.
Improved SinGAN Integrated with an Attentional Mechanism for Remote Sensing Image Classification
Authors: Gu Songwei , Zhang Rui , Luo Hongxia , Li Mengyao , Feng Huamei , Tang Xuguang
Published: April 2021

Deep learning is an important research method in the remote sensing field. However, samples of remote sensing images are relatively few in real life, and those with markers are scarce. Many neural networks represented by Generative Adversarial Networks (GANs) can learn from real samples to generate pseudosamples, rather than traditional methods that often require more time and man-power to obtain samples. However, the generated pseudosamples often have poor realism and cannot be reliably used as the basis for various analyses and applications in the field of remote sensing. To address the abovementioned problems, a pseudolabeled sample generation method is proposed in this work and applied to scene classification of remote sensing images. The improved unconditional generative model that can be learned from a single natural image (Improved SinGAN) with an attention mechanism can effectively generate enough pseudolabeled samples from a single remote sensing scene image sample. Pseudosamples generated by the improved SinGAN model have stronger realism and relatively less training time, and the extracted features are easily recognized in the classification network. The improved SinGAN can better identify sub-jects from images with complex ground scenes compared with the original network. This mechanism solves the problem of geographic errors of generated pseudosamples. This study incorporated the generated pseudosamples into training data for the classification experiment. The result showed that the SinGAN model with the integration of the attention mechanism can better guarantee feature extraction of the training data. Thus, the quality of the generated samples is improved and the classification accuracy and stability of the classification network are also enhanced.
Anisotropy Parameterization Development and Evaluation for Glacier Surface Albedo Retrieval from Satellite Observations
Authors: Ren Shaoting , Miles Evan S. , Jia Li , Menenti Massimo , Kneib Marin , Buri Pascal , McCarthy Michael J. , Shaw Thomas E. , Yang Wei , Pellicciotti Francesca
Published: April 2021

Glacier albedo determines the net shortwave radiation absorbed at the glacier surface and plays a crucial role in glacier energy and mass balance. Remote sensing techniques are efficient means to retrieve glacier surface albedo over large and inaccessible areas and to study its variability. However, corrections of anisotropic reflectance of glacier surface have been established for specific shortwave bands only, such as Landsat 5 Thematic Mapper (L5/TM) band 2 and band 4, which is a major limitation of current retrievals of glacier broadband albedo. In this study, we calibrated and evaluated four anisotropy correction models for glacier snow and ice, applicable to visible, near-infrared and shortwave-infrared wavelengths using airborne datasets of Bidirectional Reflectance Distribution Function (BRDF). We then tested the ability of the best-performing anisotropy correction model, referred to from here on as the ‘updated model’, to retrieve albedo from L5/TM, Landsat 8 Operational Land Imager (L8/OLI) and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and evaluated these results with field measurements collected on eight glaciers around the world. Our results show that the updated model: (1) can accurately estimate anisotropic factors of reflectance for snow and ice surfaces; (2) generally performs better than prior approaches for L8/OLI albedo retrieval but is not appropriate for L5/TM; (3) generally retrieves MODIS albedo better than the MODIS standard albedo product (MCD43A3) in both absolute values and glacier albedo temporal evolution, i.e., exhibiting both fewer gaps and better agreement with field observations. As the updated model enables anisotropy correction of a maximum of 10 multispectral bands and is implemented in Google Earth Engine (GEE), it is promising for observing and analyzing glacier albedo at large spatial scales.
Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets
Authors: Srivastava Ankur , Rodriguez Jose F. , Saco Patricia M. , Kumari Nikul , Yetemen Omer
Published: April 2021

Atmospheric transmissivity (τ) is a critical factor in climatology, which affects surface energy balance, measured at a limited number of meteorological stations worldwide. With the limited availability of meteorological datasets in remote areas across different climatic regions, estimation of τ is becoming a challenging task for adequate hydrological, climatic, and crop modeling studies. The availability of solar radiation data is comparatively less accessible on a global scale than the temperature and precipitation datasets, which makes it necessary to develop methods to estimate τ. Most of the previous studies provided region specific datasets of τ, which usually provide local assessments. Hence, there is a necessity to give the empirical models for τ estimation on a global scale that can be easily assessed. This study presents the analysis of the τ relationship with varying geographic features and climatic factors like latitude, aridity index, cloud cover, precipitation, temperature, diurnal temperature range, and elevation. In addition to these factors, the applicability of these relationships was evaluated for different climate types. Thus, empirical models have been proposed for each climate type to estimate τ by using the most effective factors such as cloud cover and aridity index. The cloud cover is an important yet often overlooked factor that can be used to determine the global atmospheric transmissivity. The empirical relationship and statistical indicator provided the best performance in equatorial climates as the coefficient of determination (r2) was 0.88 relatively higher than the warm temperate (r2 = 0.74) and arid regions (r2 = 0.46). According to the results, it is believed that the analysis presented in this work is applicable for estimating the τ in different ecosystems across the globe.
Evaluation Model of Remote Sensing Satellites Cooperative Observation Capability
Authors: Zheng Zhonggang , Li Qingmei , Fu Kun
Published: April 2021

This paper proposed a new remote sensing observation capability evaluation model (RSOCE) based on analytic hierarchy process to quantitatively evaluate the capability of multi-satellite cooperative remote sensing observation. The analytic hierarchical process model is a combination of qualitative and quantitative analysis of systematic decision analysis method. According to the objective of the remote sensing cooperative observation mission, we decompose the complex problem into several levels and a number of factors, compare and calculate various factors in pairs, and obtain the combination weights of different schemes. The model can be used to evaluate the observation capability of resource satellites. Taking the optical remote sensing satellites, such as China’s resource satellite series and GF-4, as examples, this paper verifies and evaluates the model for three typical tasks: point target observation, regional target observation, and moving target continuous observation. The results show that the model can provide quantitative reference and model support for comprehensive evaluation of the collaborative observation capability of remote sensing satellites.
The Making of a Joint E-Learning Platform for Remote Sensing Education: Experiences and Lessons Learned
Authors: Bauer Thomas , Immitzer Markus , Mansberger Reinfried , Vuolo Francesco , Márkus Béla , Wojtaszek Małgorzata Verőné , Földváry Lóránt , Szablowska-Midor Aneta , Kozak Jacek , Oliveira Ivan , van Lieshout Arno , Vekerdy Zoltán , Ninsawat Sarawut , Mozumder Chitrini
Published: April 2021

E-learning is widely used in academic education, and currently, the COVID-19 pandemic is increasing the demand for e-learning resources. This report describes the results achieved and the experiences gained in the Erasmus+ CBHE (Capacity Building in Higher Education) project “Innovation on Remote Sensing Education and Learning (IRSEL)”. European and Asian universities created an innovative open source e-learning platform in the field of remote sensing. Twenty modules tailored to remote sensing study programs at the four Asian partner universities were developed. Principles of remote sensing as well as specific thematic applications are part of the modules, and a knowledge pool of e-learning teaching and learning materials was created. The focus was given to case studies covering a broad range of applications. Piloting with students gave evidence about the usefulness and quality of the developed modules. In particular, teachers and students who tested the modules appreciated the balance of theory and practice. Currently, the modules are being integrated into the curricula of the participating Asian universities. The content will be available to a broader public.
A Self-Improving Framework for Joint Depth Estimation and Underwater Target Detection from Hyperspectral Imagery
Authors: Qi Jiahao , Wan Pengcheng , Gong Zhiqiang , Xue Wei , Yao Aihuan , Liu Xingyue , Zhong Ping
Published: April 2021

Underwater target detection (UTD) is one of the most attractive research topics in hyperspectral imagery (HSI) processing. Most of the existing methods are presented to predict the signatures of desired targets in an underwater context but ignore the depth information which is position-sensitive and contributes significantly to distinguishing the background and target pixels. So as to take full advantage of the depth information, in this paper a self-improving framework is proposed to perform joint depth estimation and underwater target detection, which exploits the depth information and detection results to alternately boost the final detection performance. However, it is difficult to calculate depth information under the interference of a water environment. To address this dilemma, the proposed framework, named self-improving underwater target detection framework (SUTDF), employs the spectral and spatial contextual information to pick out target-associated pixels as the guidance dataset for depth estimation work. Considering the incompleteness of the guidance dataset, an expectation-maximum liked updating scheme has also been developed to iteratively excavate the statistical and structural information from input HSI for further improving the diversity of the guidance dataset. During each updating epoch, the calculated depth information is used to yield a more diversified dataset for the target detection network, leading to a more accurate detection result. Meanwhile, the detection result will in turn contribute in detecting more target-associated pixels as the supplement for the guidance dataset, eventually promoting the capacity of the depth estimation network. With this specific self-improving framework, we can provide a more precise detection result for a hyperspectral UTD task. Qualitative and quantitative illustrations verify the effectiveness and efficiency of SUTDF in comparison with state-of-the-art underwater target detection methods.
Research on Satellite Selection Strategy for Receiver Autonomous Integrity Monitoring Applications
Authors: Wang Huibin , Cheng Yongmei , Cheng Cheng , Li Song , Li Zhenwei
Published: April 2021

Satellite selection is an effective way to overcome the challenges for the processing capability and channel limitation of the receivers due to superabundant satellites in view. The satellite selection strategies have been widely investigated to construct the subset with high accuracy but deserve further studies when applied to safety-critical applications such as the receiver autonomous integrity monitoring (RAIM) technique. In this study, the impacts of subset size on the accuracy and integrity of the subset and computation load are analyzed at first to confirm the importance of the satellite selection strategy for the RAIM process. Then the integrated performance impact of a single satellite on the current subset is evaluated according to the performance requirement of the flight phase. Subsequently, a performance-requirement-driven fast satellite selection algorithm is proposed based on the impact evaluation to construct a relatively small subset that satisfies the accuracy and integrity requirements. Comparison simulations show that the proposed algorithm can keep similar accuracy and better integrity performances than the geometric algorithm and the downdate algorithm when the subset size is fixed to 12, and can achieve an average 1.0 to 2.0 satellites smaller subset in the Lateral Navigation (LNAV) and approach procedures with vertical guidance (APV-I) horizontal requirement trial. Thus, it is suitable for real-time RAIM applications and low-cost navigation devices.
Hybrid Inversion Algorithms for Retrieval of Absorption Subcomponents from Ocean Colour Remote Sensing Reflectance
Authors: Kolluru Srinivas , Tiwari Surya Prakash , Gedam Shirishkumar S.
Published: April 2021

Semi-analytical algorithms (SAAs) invert spectral remote sensing reflectance (Rrs(λ), sr−1) to Inherent Optical Properties (IOPs) of an aquatic medium (λ is the wavelength). Existing SAAs implement different methodologies with a range of spectral IOP models and inversion methods producing concentrations of non-water constituents. Absorption spectrum decomposition algorithms (ADAs) are a set of algorithms developed to partition anw(λ), m−1 (i.e., the light absorption coefficient without pure water absorption), into absorption subcomponents of phytoplankton (aph(λ), m−1) and coloured detrital matter (adg(λ), m−1). Despite significant developments in ADAs, their applicability to remote sensing applications is rarely studied. The present study formulates hybrid inversion approaches that combine SAAs and ADAs to derive absorption subcomponents from Rrs(λ) and explores potential alternatives to operational SAAs. Using Rrs(λ) and concurrent absorption subcomponents from four datasets covering a wide range of optical properties, three operational SAAs, i.e., Garver–Siegel–Maritorena (GSM), Quasi-Analytical Algorithm (QAA), Generalized Inherent Optical Property (GIOP) model are evaluated in deriving anw(λ) from Rrs(λ). Among these three models, QAA and GIOP models derived anw(λ) with lower errors. Among six distinctive ADAs tested in the study, the Generalized Stacked Constraints Model (GSCM) and Zhang’s model-derived absorption subcomponents achieved lower average spectral mean absolute percentage errors (MAPE) in the range of 8–38%. Four hybrid models, GIOPGSCM, GIOPZhang, QAAGSCM and QAAZhang, formulated using the SAAs and ADAs, are compared for their absorption subcomponent retrieval performance from Rrs(λ). GIOPGSCM and GIOPZhang models derived absorption subcomponents have lower errors than GIOP and QAA. Potential uncertainties associated with datasets and dependency of algorithm performance on datasets were discussed.
Dual-Wavelength Polarimetric Lidar Observations of the Volcanic Ash Cloud Produced during the 2016 Etna Eruption
Authors: Mereu Luigi , Scollo Simona , Boselli Antonella , Leto Giuseppe , Zanmar Sanchez Ricardo , Bonadonna Costanza , Marzano Frank Silvio
Published: April 2021

Lidar observations are very useful to analyse dispersed volcanic clouds in the troposphere mainly because of their high range resolution, providing morphological as well as microphysical (size and mass) properties. In this work, we analyse the volcanic cloud of 18 May 2016 at Mt. Etna, in Italy, retrieved by polarimetric dual-wavelength Lidar measurements. We use the AMPLE (Aerosol Multi-Wavelength Polarization Lidar Experiment) system, located in Catania, about 25 km from the Etna summit craters, pointing at a thin volcanic cloud layer, clearly visible and dispersed from the summit craters at the altitude between 2 and 4 km and 6 and 7 km above the sea level. Both the backscattering and linear depolarization profiles at 355 nm (UV, ultraviolet) and 532 nm (VIS, visible) wavelengths, respectively, were obtained using different angles at 20°, 30°, 40° and 90°. The proposed approach inverts the Lidar measurements with a physically based inversion methodology named Volcanic Ash Lidar Retrieval (VALR), based on Maximum-Likelihood (ML). VALRML can provide estimates of volcanic ash mean size and mass concentration at a resolution of few tens of meters. We also compared those results with two methods: Single-variate Regression (SR) and Multi-variate Regression (MR). SR uses the backscattering coefficient or backscattering and depolarization coefficients of one wavelength (UV or VIS in our cases). The MR method uses the backscattering coefficient of both wavelengths (UV and VIS). In absence of in situ airborne validation data, the discrepancy among the different retrieval techniques is estimated with respect to the VALR ML algorithm. The VALR ML analysis provides ash concentrations between about 0.1 μg/m3 and 1 mg/m3 and particle mean sizes of 0.1 μm and 6 μm, respectively. Results show that, for the SR method differences are less than <10%, using the backscattering coefficient only and backscattering and depolarization coefficients. Moreover, we find differences of 20–30% respect to VALR ML, considering well-known parametric retrieval methods. VALR algorithms show how a physics-based inversion approaches can effectively exploit the spectral-polarimetric Lidar AMPLE capability.
Remote Sensing-Based Analysis of Spatial and Temporal Water Colour Variations in Baiyangdian Lake after the Establishment of the Xiong’an New Area
Authors: Zhao Yelong , Wang Shenglei , Zhang Fangfang , Shen Qian , Li Junsheng , Yang Fan
Published: April 2021

The Forel-Ule Index (FUI) is an important parameter that can be calculated from optical remote sensing data to assess water quality based on water colour. Using Sentinel-2 images from April to November within the 2016–2020 period coupled with the Google Earth Engine Platform, we calculated FUI to analyse the spatial distribution, seasonal variations, and inter-annual variations of water colour in Baiyangdian Lake in the Xiong’an New Area established on 1 April 2017. The lake was divided into seven sub-regions, A–G; subsequently, high and low FUI values were observed in the south and north, respectively. Additionally, the mean FUI values of G and F zones in the south were 11.9 and 12.7, respectively, whereas those for the A, B, C, D, and E zones in the north were 10.5, 9.8, 10.4, 11.1, 11.2, respectively. The seasonal variations in the Baiyangdian Lake and seven sub-regions were consistent, with turbid water in spring and autumn, and clear water in summer. Inter-annual variations analyses for 2016–2020 indicated that the zone of A became progressively turbid, whereas the B, C, D, E, F, and G zones exhibited slow and gradually decreasing trends. Our findings suggest that the overall water quality of Baiyangdian Lake may be better, which may be related to the governance policies of the region.
Validity of Inertial Sensors for Assessing Balance Kinematics and Mobility during Treadmill-Based Perturbation and Dance Training
Authors: Ofori Ernest Kwesi , Wang Shuaijie , Bhatt Tanvi
Published: April 2021

Inertial sensors (IS) enable the kinematic analysis of human motion with fewer logistical limitations than the silver standard optoelectronic motion capture (MOCAP) system. However, there are no data on the validity of IS for perturbation training and during the performance of dance. The aim of this present study was to determine the concurrent validity of IS in the analysis of kinematic data during slip and trip-like perturbations and during the performance of dance. Seven IS and the MOCAP system were simultaneously used to capture the reactive response and dance movements of fifteen healthy young participants (Age: 18–35 years). Bland Altman (BA) plots, root mean square errors (RMSE), Pearson’s correlation coefficients (R), and intraclass correlation coefficients (ICC) were used to compare kinematic variables of interest between the two systems for absolute equivalency and accuracy. Limits of agreements (LOA) of the BA plots ranged from −0.23 to 0.56 and −0.21 to 0.43 for slip and trip stability variables, respectively. The RMSE for slip and trip stabilities were from 0.11 to 0.20 and 0.11 to 0.16, respectively. For the joint mobility in dance, LOA varied from −6.98–18.54, while RMSE ranged from 1.90 to 13.06. Comparison of IS and optoelectronic MOCAP system for reactive balance and body segmental kinematics revealed that R varied from 0.59 to 0.81 and from 0.47 to 0.85 while ICC was from 0.50 to 0.72 and 0.45 to 0.84 respectively for slip–trip perturbations and dance. Results of moderate to high concurrent validity of IS and MOCAP systems. These results were consistent with results from similar studies. This suggests that IS are valid tools to quantitatively analyze reactive balance and mobility kinematics during slip–trip perturbation and the performance of dance at any location outside, including the laboratory, clinical and home settings.