bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanisms of Silver Nanoparticle Uptake by Embryonic Zebrafish Cells
Authors: Quevedo Ana , Ellis Laura-Jayne , Lynch Iseult , Valsami-Jones Eugenia
Published: October 2021

Evaluation of the uptake pathways in cells during exposure to nanoparticles (NPs) is key for risk assessment and the development of safer nanomaterials, as the internalisation and fate of NPs is linked to their toxicity and mode of action. Here, we determined the uptake mechanisms activated during the internalisation of 10, 30, and 100 nm AgNPs by embryonic zebrafish cells (ZF4). The uptake results demonstrated an NP size- and time-dependent uptake, showing the highest total silver uptake for the smallest AgNP (10 nm) at the lowest exposure concentration (2.5 μg/mL) after 2 h, while after 24 h, the highest exposure concentration (10 μg/mL) of the 10 nm AgNPs revealed the highest cellular load at 8 pg/cell. Inhibition of the caveolae, clathrin, and macropinocytosis endocytic pathways by pharmaceutical inhibitors (genistein, chlorpromazine, and wortmannin respectively) revealed that uptake was mainly via macropinocytosis for the 10 nm AgNPs and via the caveolae-mediated pathway for the 30 and 100 nm AgNPs. The induction of autophagy was also strongly related to the NP size, showing the highest percentage of induction for the 10 nm (around 3%) compared to naive cells, suggesting that autophagy can be activated along with endocytosis to deal with exposure to NPs. TEM imaging revealed the distribution of NPs across the cytoplasm inside intracellular vesicles. An increase in Early Endosome formation (EE) was observed for the 30 and 100 nm sizes, whereas the 10 nm AgNPs disrupted the activity of EE. The data supports the establishment of adverse outcome pathways by increasing knowledge on the link between a molecular initiating event such as receptor-mediated endocytosis and an adverse outcome, as well as supporting the reduction of animal testing by using alternative testing models, such as fish cell lines.
Copper and Copper/Zn Ratio in a Series of Children with Chronic Diseases: A Cross-Sectional Study
Authors: Escobedo-Monge Marlene , Barrado Enrique , Parodi-Román Joaquín , Escobedo-Monge María , Torres-Hinojal María , Marugán-Miguelsanz José
Published: October 2021

Copper is an essential micronutrient for humans. A cross-sectional and comparative study was done to assess serum Cu levels and serum copper/zinc (Cu/Zn) ratio and its association with nutritional indicators in a series of children and adolescents with chronic diseases. Anthropometric, biochemical, dietary, body composition, and bone densitometry assessments were carried out. Serum Cu and Zn were measured by atomic absorption spectrophotometry. Seventy-eight patients (55% women) participated. The mean serum Cu in the entire series and by nutritional status through body mass index (BMI) was normal. Serum Cu decreased significantly with age and was meaningfully higher in children than in adolescents. The risk of finding altered Cu levels in children and men was higher than in adolescents and women, respectively. Twenty-two per cent of patients had abnormal serum copper levels, 13 had hypercupremia, and four had hypocupremia. The Cu/Zn ratio was greater than 1.00 for 87% of the patients, which is an indicator of an inflammatory state. All patients with hypozincemia and hypocupremia had deficient Zn intake, but only 65% of the patients with hypercupremia had dietary Zn deficiency. Consequently, the Cu/Zn ratio could indicate an inflammatory state and a high risk of zinc deficiency in this specific child population.
FTO and PLAG1 Genes Expression and FTO Methylation Predict Changes in Circulating Levels of Adipokines and Gastrointestinal Peptides in Children
Authors: Czogała Wojciech , Strojny Wojciech , Schab Magdalena , Grabowska Agnieszka , Miklusiak Karol , Kowalczyk Wojciech , Łazarczyk Agnieszka , Tomasik Przemysław , Skoczeń Szymon
Published: October 2021

Adipokines and gastrointestinal tract hormones are important metabolic parameters, and both epigenetic factors and differential gene expression patterns may be associated with the alterations in their concentrations in children. The function of the FTO gene (FTO alpha-ketoglutarate dependent dioxygenase) in the regulation of the global metabolic rate is well described, whereas the influence of protooncogene PLAG1 (PLAG1 zinc finger) is still not fully understood. A cross-sectional study on a group of 26 children with various BMI values (15.3–41.7; median 28) was carried out. The aim was to evaluate the dependencies between the level of methylation and expression of aforementioned genes with the concentration of selected gastrointestinal tract hormones and adipokines in children. Expression and methylation were measured in peripheral blood mononuclear DNA by a microarray technique and a restriction enzyme method, respectively. All peptide concentrations were determined using the enzyme immunoassay method. The expression level of both FTO and PLAG1 genes was statistically significantly related to the concentration of adipokines: negatively for apelin and leptin receptor, and positively for leptin. Furthermore, both FTO methylation and expression negatively correlated with the concentration of resistin and visfatin. Cholecystokinin was negatively correlated, whereas fibroblast growth factor 21 positively correlated with methylation and expression of the FTO gene, while FTO and PLAG1 expression was negatively associated with the level of cholecystokinin and glucagon-like peptide-1. The PLAG1 gene expression predicts an increase in leptin and decrease in ghrelin levels. Our results indicate that the FTO gene correlates with the concentration of hormones produced by the adipose tissue and gastrointestinal tract, and PLAG1 gene may be involved in adiposity pathogenesis. However, the exact molecular mechanisms still need to be clarified.
Relationships between Pre-Stroke SARC-F Scores, Disability, and Risk of Malnutrition and Functional Outcomes after Stroke—A Prospective Cohort Study
Authors: Nozoe Masafumi , Kubo Hiroki , Kanai Masashi , Yamamoto Miho
Published: October 2021

SARC-F is a screening tool for sarcopenia; however, it has not yet been established whether SARC-F scores predict functional outcomes. Therefore, we herein investigated the relationship between SARC-F scores and functional outcomes in stroke patients. The primary outcome in the present study was the modified Rankin Scale (mRS) 3 months after stroke. The relationship between SARC-F scores and poor functional outcomes was examined using a logistic regression analysis. Furthermore, the applicability of SARC-F scores to the assessment of poor functional outcomes was analyzed based on the area under the receiver operating curve (ROC). Eighty-one out of the 324 patients enrolled in the present study (25%) had poor functional outcomes (mRS ≥ 4). The results of the multivariate analysis revealed a correlation between SARC-F scores (OR = 1.29, 95% CI = 1.05–1.59, p = 0.02) and poor functional outcomes. A cut-off SARC-F score ≥ 4 had low-to-moderate sensitivity (47.4%) and high specificity (87.3%). The present results suggest that the measurement of pre-stroke SARC-F scores is useful for predicting the outcomes of stroke patients.
Short Communication: Latent Detection of Downy Mildew (Peronospora pisi) in Bioassays against Pisum sativum
Authors: Marr Alexia , Casonato Seona , Jones Eirian
Published: October 2021

Downy mildew of peas is caused by the obligate parasite Peronospora pisi, which occurs sporadically throughout temperate pea-growing regions across the world. To screen pea lines against this biotrophic pathogen, a suitable and reproducible in vitro method using living plant material is required. Field screening can be influenced by environmental factors, thus giving variable results. The aim of this study was to develop a method that could reliably be used to screen pea cultivars against P. pisi in a laboratory setting. A range of bioassays were used to test various methods of inoculation, utilizing sporangia and naturally infested soil. Latent infection was achieved by planting seeds in soil collected from a site with a known history of P. pisi infection and directly inoculating young pea plants with sporangia. Out of the 108 plants which survived the experimental period, only two plants expressed visible signs of disease; however, through a two-step nested PCR process we detected latent infection in 24 plants. This research highlights the importance of considering the presence of latent infection when screening pea lines against downy mildew.
Molecular Identification of Selected Tick-Borne Protozoan and Bacterial Pathogens in Thoroughbred Racehorses in Cavite, Philippines
Authors: Galon Eloiza May , Macalanda Adrian Miki , Garcia Mary Margarett , Ibasco Chrysler James , Garvida Anatolio , Ji Shengwei , Zafar Iqra , Hasegawa Yae , Liu Mingming , Ybañez Rochelle Haidee , Umemiya-Shirafuji Rika , Ybañez Adrian , Claveria Florencia , Xuan Xuenan
Published: October 2021

Tick-borne diseases (TBDs) considerably impair equine health and productivity. Moreover, TBDs, particularly equine piroplasmosis, impede international movement and trade of equids, which is a vital component of the global horse racing industry. In the Philippines, horse racing is a lucrative industry generating millions of USD annually. However, information on equine TBDs is scarce. This study intended to describe molecularly the equine tick-borne infections in a racehorse park in Cavite, Philippines and identify the risk factors associated with the infections. One hundred twenty-four (n = 124) thoroughbred racehorses were sampled and screened for selected tick-borne protozoan and bacterial pathogens using polymerase chain reaction (PCR) assays. Racehorses were positive for Babesia caballi (12.10%; 15/124), Theileria equi (0.81%; 1/124), Anaplasma phagocytophilum (10.48%; 13/124), Borrelia burgdorferi sensu lato (38.71%; 48/124), A. marginale (0.81%; 1/124), and Coxiella burnetii (0.81%; 1/124). Rickettsia was not detected in the samples. Gender was determined as a significant risk factor for B. caballi infection. Sequencing analysis revealed that seven partial 18S rRNA B. caballi isolates shared 98.63–100% identity with each other and were classified as genotype A. Meanwhile, the sequence obtained from the lone T. equi-positive sample was 99.77% identical to isolates from Spain, Switzerland, China, Saudi Arabia, and South Korea, and was confirmed as genotype E based on the 18S rRNA gene. Eight Anaplasma 16S rRNA partial sequences were highly identical to A. phagocytophilum and A. ovis. Partial sequences of Borrelia 5–23S rRNA were most closely related to B. japonica and other Borrelia sp. isolates from various countries. This study reports the first molecular detection of Borrelia and Anaplasma and the identification of B. caballi and T. equi genotypes in racehorses in the Philippines. Findings from this study shall be useful in crafting equine tick and TBD control and prevention programs in the country.
Plasma Rich in Growth Factors in the Treatment of Endodontic Periapical Lesions in Adult Patients: A Narrative Review
Authors: Zoltowska Agata , Machut Katarzyna , Pawlowska Elzbieta , Derwich Marcin
Published: October 2021

Platelet concentrates have been widely used in regenerative medicine, including endodontics. The aim of this manuscript was to assess critically the efficacy of PRF in the treatment of endodontic periapical lesions in adult patients on the basis of the literature. The PICO approach was used to properly develop literature search strategies. The PubMed database was analyzed with the keywords: “((PRP) OR (PRF) OR (PRGF) OR (CGF)) AND (endodontic) AND ((treatment) OR (therapy))”. After screening of 155 results, 14 articles were included in this review. Different types of platelet concentrates are able to stimulate the processes of proliferation and differentiation of mesenchymal stem cells. Platelet rich fibrin (PRF) releases growth factors for at least 7 days at the application site. Growth factors and released cytokines stimulate the activity of osteoblasts. Moreover, the release of growth factors accelerates tissue regeneration by increasing the migration of fibroblasts. It was not possible to assess the efficacy of PRF supplementation in the treatment of endodontic periapical lesions in permanent, mature teeth with closed apexes, due to the lack of well-designed scientific research. Further studies are needed to analyze the effect of PRF on the healing processes in the periapical region.
Ten-Year Outcomes of Intravitreal Bevacizumab for Myopic Choroidal Neovascularization: Analysis of Prognostic Factors
Authors: Mallone Fabiana , Giustolisi Rosalia , Franzone Federica , Marenco Marco , Plateroti Rocco , Nebbioso Marcella , Lambiase Alessandro , Gharbiya Magda
Published: October 2021

The current standard treatment of myopic choroidal neovascularisation (mCNV) is intravitreal injection of VEGF antagonists. This study was proposed to assess efficacy and safety of intravitreal bevacizumab (IVB) for the treatment of mCNV across a 10-year follow-up. Thirty eyes of thirty patients with treatment-naïve mCNV who underwent IVB and were followed up with for a minimum of ten years were recruited for the present retrospective cohort study. All participants were treated with three monthly IVB at baseline and then evaluated and treated under pro re nata (PRN) schedule. Outcome measures were to determine BCVA changes over years and identify the predictive factors of both final visual outcome and need for retreatment. Analysis of the main involved prognostic factors with correlations among variables is reported. Visual acuity remained stable at 10-year follow-up (p = 0.001) with the greatest improvement at 2 years (p < 0.0001) in all CNV locations. Baseline BCVA correlated positively with final BCVA (β = 0.88, p < 0.0001, R2: 0.75). No predictive factors for the need of additional injections were identified. Retinal and choroidal thickness significantly reduced over time but without correlation with the number of injections. CNV max height and area significantly decreased at 10 years (p < 0.0001 and p = 0.003, respectively), with complete regression of mCNV lesion in 40% of subjects. Intravitreal bevacizumab resulted as long-term effective and safe therapy for mCNV with sustained results at 10 years.
Esculetin Provides Neuroprotection against Mutant Huntingtin-Induced Toxicity in Huntington’s Disease Models
Authors: Pruccoli Letizia , Breda Carlo , Teti Gabriella , Falconi Mirella , Giorgini Flaviano , Tarozzi Andrea
Published: October 2021

Huntington’s disease (HD) is a neurodegenerative disorder caused by an abnormal CAG trinucleotide repeat expansion within exon 1 of the huntingtin (HTT) gene. This mutation leads to the production of mutant HTT (mHTT) protein which triggers neuronal death through several mechanisms. Here, we investigated the neuroprotective effects of esculetin (ESC), a bioactive phenolic compound, in an inducible PC12 model and a transgenic Drosophila melanogaster model of HD, both of which express mHTT fragments. ESC partially inhibited the progression of mHTT aggregation and reduced neuronal death through its ability to counteract the oxidative stress and mitochondria impairment elicited by mHTT in the PC12 model. The ability of ESC to counteract neuronal death was also confirmed in the transgenic Drosophila model. Although ESC did not modify the lifespan of the transgenic Drosophila, it still seemed to have a positive impact on the HD phenotype of this model. Based on our findings, ESC may be further studied as a potential neuroprotective agent in a rodent transgenic model of HD.
Functionalized Nanoparticles Targeting Tumor-Associated Macrophages as Cancer Therapy
Authors: He Yuanyuan , de Araújo Júnior Raimundo Fernandes , Cruz Luis J. , Eich Christina
Published: October 2021

The tumor microenvironment (TME) plays a central role in regulating antitumor immune responses. As an important part of the TME, alternatively activated type 2 (M2) macrophages drive the development of primary and secondary tumors by promoting tumor cell proliferation, tumor angiogenesis, extracellular matrix remodeling and overall immunosuppression. Immunotherapy approaches targeting tumor-associated macrophages (TAMs) in order to reduce the immunosuppressive state in the TME have received great attention. Although these methods hold great potential for the treatment of several cancers, they also face some limitations, such as the fast degradation rate of drugs and drug-induced cytotoxicity of organs and tissues. Nanomedicine formulations that prevent TAM signaling and recruitment to the TME or deplete M2 TAMs to reduce tumor growth and metastasis represent encouraging novel strategies in cancer therapy. They allow the specific delivery of antitumor drugs to the tumor area, thereby reducing side effects associated with systemic application. In this review, we give an overview of TAM biology and the current state of nanomedicines that target M2 macrophages in the course of cancer immunotherapy, with a specific focus on nanoparticles (NPs). We summarize how different types of NPs target M2 TAMs, and how the physicochemical properties of NPs (size, shape, charge and targeting ligands) influence NP uptake by TAMs in vitro and in vivo in the TME. Furthermore, we provide a comparative analysis of passive and active NP-based TAM-targeting strategies and discuss their therapeutic potential.
Biodegradation of Different Types of Plastics by Tenebrio molitor Insect
Authors: Bulak Piotr , Proc Kinga , Pytlak Anna , Puszka Andrzej , Gawdzik Barbara , Bieganowski Andrzej
Published: October 2021

Looking for new, sustainable ways to utilize plastics is still a very pertinent topic considering the amount of plastics produced in the world. One of the newest and intriguing possibility is the use of insects in biodegradation of plastics, which can be named entomoremediation. The aim of this work was to demonstrate the ability of the insect Tenebrio molitor to biodegrade different, real plastic waste. The types of plastic waste used were: remains of thermal building insulation polystyrene foam (PS), two types of polyurethane (kitchen sponge as PU1 and commercial thermal insulation foam as PU2), and polyethylene foam (PE), which has been used as packaging material. After 58 days, the efficiency of mass reduction for all of the investigated plastics was 46.5%, 41.0%, 53.2%, and 69.7% for PS, PU1, PU2, and PE, respectively (with a dose of 0.0052 g of each plastic per 1 mealworm larvae). Both larvae and imago were active plastic eaters. However, in order to shorten the duration of the experiment and increase the specific consumption rate, the two forms of the insect should not be combined together in one container.
Electrical Characterization of Thin PEDOT:PSS Films on Alumina and Thiol–Ene Substrates
Authors: Jucius Dalius , Gudaitis Rimantas , Lazauskas Algirdas , Grigaliūnas Viktoras
Published: October 2021

Transparent polymer layers that heal minor scratches and maintain the optical properties of the devices for a long time are highly desirable in optoelectronics. This paper presents the results of the electrical characterization of thin PEDOT:PSS films on the novel, optically transparent thiol–ene substrates capable of healing scratches under room-temperature conditions. Electrical properties of the PEDOT:PSS films deposited on the conventional alumina ceramic substrates were also tested for comparative purposes. This study demonstrated that the substrate can have a significant effect on the electrical properties of PEDOT:PSS films, and the electrical resistance of the films on thiol–ene substrates is not as stable as on alumina ceramics. However, the changes in electrical resistance of the films on thiol–ene are small enough over a sufficiently wide range of operating temperatures and relative humidities and allow the application of such bilayers in various polymeric optoelectronic devices.
Study on Control of Polymeric Architecture of Sulfonated Hydrocarbon-Based Polymers for High-Performance Polymer Electrolyte Membranes in Fuel Cell Applications
Authors: Kim Mijeong , Ko Hansol , Nam Sang Yong , Kim Kihyun
Published: October 2021

Polymer electrolyte membrane fuel cell (PEMFC) is an eco-friendly energy conversion device that can convert chemical energy into electrical energy without emission of harmful oxidants such as nitrogen oxides (NOx) and/or sulfur oxides (SOx) during operation. Nafion®, a representative perfluorinated sulfonic acid (PFSA) ionomer-based membrane, is generally incorporated in fuel cell systems as a polymer electrolyte membrane (PEM). Since the PFSA ionomers are composed of flexible hydrophobic main backbones and hydrophilic side chains with proton-conducting groups, the resulting membranes are found to have high proton conductivity due to the distinct phase-separated structure between hydrophilic and hydrophobic domains. However, PFSA ionomer-based membranes have some drawbacks, including high cost, low glass transition temperatures and emission of environmental pollutants (e.g., HF) during degradation. Hydrocarbon-based PEMs composed of aromatic backbones with proton-conducting hydrophilic groups have been actively studied as substitutes. However, the main problem with the hydrocarbon-based PEMs is the relatively low proton-conducting behavior compared to the PFSA ionomer-based membranes due to the difficulties associated with the formation of well-defined phase-separated structures between the hydrophilic and hydrophobic domains. This study focused on the structural engineering of sulfonated hydrocarbon polymers to develop hydrocarbon-based PEMs that exhibit outstanding proton conductivity for practical fuel cell applications.
Laser-Induced Microstructuring of Polymers in Gaseous, Liquid and Supercritical Media
Authors: Rybaltovskii Alexey , Minaev Nikita , Tsypina Svetlana , Minaeva Svetlana , Yusupov Vladimir
Published: October 2021

New results are presented for laser formation—in particular, the “drawing” of microstructures in polymer films using continuous-wave (CW) laser radiation λ = 405 nm with an intensity of 0.8–3.7 kW/cm2. The laser drawing was carried out in the polymer system poly-2,2′-p-oxydiphenylene-5,5′-bis-benzimidazole (OPBI), which consists of two phases: a solid polymer matrix with formic acid (HCOOH) dissolved in it. The formation of microstructures, including the stage of foaming, was carried out in three media: air, water and a supercritical carbon dioxide medium containing dissolved molecules of the silver precursor Ag(hfac)COD. The morphological features of foam-like track structures formed in the near-surface layer of the polymer films by laser “drawing” are considered. A model of processes is presented that explains the appearance of periodic structures. The key point of this model is that it considers the participation of the photoinduced mechanism of explosive boiling of formic acid molecules dissolved in the polymer matrix. Using Raman spectroscopy, spectra were obtained and interpreted, which relate to different stages in the formation of microstructures in OPBI films. The effects associated with the peculiarities of luminescent microstructures on the surfaces of glasses in close contact with polymer films during laser “painting” in the air have been studied.
Experimental Evaluation of Axial Reaction Turbine Stage Bucket Losses
Authors: Klimko Marek , Lenhard Richard , Žitek Pavel , Kaduchová Katarína
Published: October 2021

The article describes the measurement methods and data evaluation from a single-stage axial turbine with high reaction (50%). Four operating modes of the turbine were selected, in which the wake traversing behind nozzle and bucket with five-hole pneumatic probes took place. The article further focuses on the evaluation of bucket losses for all four measured operating modes, including the analysis of measurement uncertainties.
From Geometry to Coherent Dissipative Dynamics in Quantum Mechanics
Authors: Cruz-Prado Hans , Bravetti Alessandro , Garcia-Chung Angel
Published: October 2021

Starting from the geometric description of quantum systems, we propose a novel approach to time-independent dissipative quantum processes according to which energy is dissipated but the coherence of the states is preserved. Our proposal consists of extending the standard symplectic picture of quantum mechanics to a contact manifold and then obtaining dissipation by using appropriate contact Hamiltonian dynamics. We work out the case of finite-level systems for which it is shown, by means of the corresponding contact master equation, that the resulting dynamics constitute a viable alternative candidate for the description of this subclass of dissipative quantum systems. As a concrete application, motivated by recent experimental observations, we describe quantum decays in a 2-level system as coherent and continuous processes.
A “Sloppy Wet Kiss”? Intralingual Translation and Meaning-Making in Contemporary Congregational Songs
Authors: Thornton Daniel
Published: October 2021

Translation as a form of music localization does not only occur in diverse cultural or lingual contexts, it also occurs within an ostensibly homogenous culture and language. The global genre of contemporary congregational songs (CCS) is written and performed through a variety of theological lenses. Sometimes a theological position conveyed in, or ascribed to, CCS can be problematic for certain local expressions of the Christian faith to replicate without needing to alter lyrics, and/or musical content, or at least reinterpret those lyrics in a way which aligns with their theological understanding. This article explores popular CCS, as measured by Christian Copyright Licensing International (CCLI) which have been either accepted, rejected, reinterpreted, or otherwise altered in order to play their part in defining local (English-speaking) church worship and identity. Translation studies and music semiology are applied to selected CCS to demonstrate this nuanced interpretation of “translation” in the localizing of religious musical practice
Classifying Major Explosions and Paroxysms at Stromboli Volcano (Italy) from Space
Authors: Corradino Claudia , Amato Eleonora , Torrisi Federica , Calvari Sonia , Del Negro Ciro
Published: October 2021

Stromboli volcano has a persistent activity that is almost exclusively explosive. Predominated by low intensity events, this activity is occasionally interspersed with more powerful episodes, known as major explosions and paroxysms, which represent the main hazards for the inhabitants of the island. Here, we propose a machine learning approach to distinguish between paroxysms and major explosions by using satellite-derived measurements. We investigated the high energy explosive events occurring in the period January 2018–April 2021. Three distinguishing features are taken into account, namely (i) the temporal variations of surface temperature over the summit area, (ii) the magnitude of the explosive volcanic deposits emplaced during each explosion, and (iii) the height of the volcanic ash plume produced by the explosive events. We use optical satellite imagery to compute the land surface temperature (LST) and the ash plume height (PH). The magnitude of the explosive volcanic deposits (EVD) is estimated by using multi-temporal Synthetic Aperture Radar (SAR) intensity images. Once the input feature vectors were identified, we designed a k-means unsupervised classifier to group the explosive events at Stromboli volcano based on their similarities in two clusters: (1) paroxysms and (2) major explosions. The major explosions are identified by low/medium thermal content, i.e., LSTI around 1.4 °C, low plume height, i.e., PH around 420 m, and low production of explosive deposits, i.e., EVD around 2.5. The paroxysms are extreme events mainly characterized by medium/high thermal content, i.e., LSTI around 2.3 °C, medium/high plume height, i.e., PH around 3330 m, and high production of explosive deposits, i.e., EVD around 10.17. The centroids with coordinates (PH, EVD, LSTI) are: Cp (3330, 10.7, 2.3) for the paroxysms, and Cme (420, 2.5, 1.4) for the major explosions.
SMOS Brightness Temperature Monitoring Quality Control Review and Enhancements
Authors: Weston Peter , de Rosnay Patricia
Published: October 2021

Brightness temperature (Tb) observations from the European Space Agency (ESA) Soil Moisture Ocean Salinity (SMOS) instrument are passively monitored in the European Centre for Medium-range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). Several quality control procedures are performed to screen out poor quality data and/or data that cannot accurately be simulated from the numerical weather prediction (NWP) model output. In this paper, these quality control procedures are reviewed, and enhancements are proposed, tested, and evaluated. The enhancements presented include improved sea ice screening, coastal and ambiguous land-ocean screening, improved radio frequency interference (RFI) screening, and increased usage of observation at the edge of the satellite swath. Each of the screening changes results in improved agreement between the observations and model equivalent values. This is an important step in advance of future experiments to test the direct assimilation of SMOS Tbs into the ECMWF land data assimilation system.
Spatial Analysis of Urban Residential Sensitivity to Heatwave Events: Case Studies in Five Megacities in China
Authors: Zhi Guoqing , Meng Bin , Wang Juan , Chen Siyu , Tian Bin , Ji Huimin , Yang Tong , Wang Bingqing , Liu Jian
Published: October 2021

Urban heatwaves increase residential health risks. Identifying urban residential sensitivity to heatwave risks is an important prerequisite for mitigating the risks through urban planning practices. This research proposes a new paradigm for urban residential sensitivity to heatwave risks based on social media Big Data, and describes empirical research in five megacities in China, namely, Beijing, Nanjing, Wuhan, Xi’an and Guangzhou, which explores the application of this paradigm to real-world environments. Specifically, a method to identify urban residential sensitive to heatwave risks was developed by using natural language processing (NLP) technology. Then, based on remote sensing images and Weibo data, from the perspective of the relationship between people (group perception) and the ground (meteorological temperature), the relationship between high temperature and crowd sensitivity in geographic space was studied. Spatial patterns of the residential sensitivity to heatwaves over the study area were characterized at fine scales, using the information extracted from remote sensing information, spatial analysis, and time series analysis. The results showed that the observed residential sensitivity to urban heatwave events (HWEs), extracted from Weibo data (Chinese Twitter), best matched the temporal trends of HWEs in geographic space. At the same time, the spatial distribution of observed residential sensitivity to HWEs in the cities had similar characteristics, with low sensitivity in the urban center but higher sensitivity in the countryside. This research illustrates the benefits of applying multi-source Big Data and intelligent analysis technologies to the understand of impacts of heatwave events on residential life, and provide decision-making data for urban planning and management.
A Novel Approach for Forest Fragmentation Susceptibility Mapping and Assessment: A Case Study from the Indian Himalayan Region
Authors: Batar Amit Kumar , Shibata Hideaki , Watanabe Teiji
Published: October 2021

An estimation of where forest fragmentation is likely to occur is critically important for improving the integrity of the forest landscape. We prepare a forest fragmentation susceptibility map for the first time by developing an integrated model and identify its causative factors in the forest landscape. Our proposed model is based upon the synergistic use of the earth observation data, forest fragmentation approach, patch forests, causative factors, and the weight-of-evidence (WOE) method in a Geographical Information System (GIS) platform. We evaluate the applicability of the proposed model in the Indian Himalayan region, a region of rich biodiversity and environmental significance in the Indian subcontinent. To obtain a forest fragmentation susceptibility map, we used patch forests as past evidence of completely degraded forests. Subsequently, we used these patch forests in the WOE method to assign the standardized weight value to each class of causative factors tested by the Variance Inflation Factor (VIF) method. Finally, we prepare a forest fragmentation susceptibility map and classify it into five levels: very low, low, medium, high, and very high and test its validity using 30% randomly selected patch forests. Our study reveals that around 40% of the study area is highly susceptible to forest fragmentation. This study identifies that forest fragmentation is more likely to occur if proximity to built-up areas, roads, agricultural lands, and streams is low, whereas it is less likely to occur in higher altitude zones (more than 2000 m a.s.l.). Additionally, forest fragmentation will likely occur in areas mainly facing south, east, southwest, and southeast directions and on very gentle and gentle slopes (less than 25 degrees). This study identifies Himalayan moist temperate and pine forests as being likely to be most affected by forest fragmentation in the future. The results suggest that the study area would experience more forest fragmentation in the future, meaning loss of forest landscape integrity and rich biodiversity in the Indian Himalayan region. Our integrated model achieved a prediction accuracy of 88.7%, indicating good accuracy of the model. This study will be helpful to minimize forest fragmentation and improve the integrity of the forest landscape by implementing forest restoration and reforestation schemes.
A Comparative Estimation of Maize Leaf Water Content Using Machine Learning Techniques and Unmanned Aerial Vehicle (UAV)-Based Proximal and Remotely Sensed Data
Authors: Ndlovu Helen S. , Odindi John , Sibanda Mbulisi , Mutanga Onisimo , Clulow Alistair , Chimonyo Vimbayi G. P. , Mabhaudhi Tafadzwanashe
Published: October 2021

Determining maize water content variability is necessary for crop monitoring and in developing early warning systems to optimise agricultural production in smallholder farms. However, spatially explicit information on maize water content, particularly in Southern Africa, remains elementary due to the shortage of efficient and affordable primary sources of suitable spatial data at a local scale. Unmanned Aerial Vehicles (UAVs), equipped with light-weight multispectral sensors, provide spatially explicit, near-real-time information for determining the maize crop water status at farm scale. Therefore, this study evaluated the utility of UAV-derived multispectral imagery and machine learning techniques in estimating maize leaf water indicators: equivalent water thickness (EWT), fuel moisture content (FMC), and specific leaf area (SLA). The results illustrated that both NIR and red-edge derived spectral variables were critical in characterising the maize water indicators on smallholder farms. Furthermore, the best models for estimating EWT, FMC, and SLA were derived from the random forest regression (RFR) algorithm with an rRMSE of 3.13%, 1%, and 3.48%, respectively. Additionally, EWT and FMC yielded the highest predictive performance and were the most optimal indicators of maize leaf water content. The findings are critical towards developing a robust and spatially explicit monitoring framework of maize water status and serve as a proxy of crop health and the overall productivity of smallholder maize farms.
Forest Cover and Sustainable Development in the Lumbini Province, Nepal: Past, Present and Future
Authors: Rimal Bhagawat , Keshtkar Hamidreza , Stork Nigel , Rijal Sushila
Published: October 2021

The analysis of forest cover change at different scales is an increasingly important research topic in environmental studies. Forest Landscape Restoration (FLR) is an integrated approach to manage and restore forests across various landscapes and environments. Such restoration helps to meet the targets of Sustainable Development Goal (SDG)–15, as outlined in the UN Environment’s sixth Global Outlook, which includes the sustainable management of forests, the control of desertification, reducing degradation, biodiversity loss, and the conservation of mountain ecosystems. Here, we have used time series Landsat images from 1996 to 2016 to see how land use, and in particular forest cover, have changed between 1996 and 2016 in the Lumbini Province of Nepal. In addition, we simulated projections of land cover (LC) and forest cover change for the years 2026 and 2036 using a hybrid cellular automata Markov chain (CA–Markov) model. We found that the overall forest area increased by 199 km2 (2.1%), from a 9491 km2 (49.3%) area in 1996 to 9691 km2 (50.3%) area in 2016. Our modeling suggests that forest area will increase by 81 km2 (9691 to 9772 km2) in 2026 and by 195 km2 (9772 km2 to 9966 km2) in 2036. They are policy, planning, management factors and further strategies to aid forest regeneration. Clear legal frameworks and coherent policies are required to support sustainable forest management programs. This research may support the targets of the Sustainable Development Goals (SDG), the land degradation neutral world (LDN), and the UN decade 2021–2031 for ecosystem restoration.
Hyperspectral Image Mixed Noise Removal Using Subspace Representation and Deep CNN Image Prior
Authors: Zhuang Lina , Ng Michael K. , Fu Xiyou
Published: October 2021

The ever-increasing spectral resolution of hyperspectral images (HSIs) is often obtained at the cost of a decrease in the signal-to-noise ratio (SNR) of the measurements. The decreased SNR reduces the reliability of measured features or information extracted from HSIs, thus calling for effective denoising techniques. This work aims to estimate clean HSIs from observations corrupted by mixed noise (containing Gaussian noise, impulse noise, and dead-lines/stripes) by exploiting two main characteristics of hyperspectral data, namely low-rankness in the spectral domain and high correlation in the spatial domain. We take advantage of the spectral low-rankness of HSIs by representing spectral vectors in an orthogonal subspace, which is learned from observed images by a new method. Subspace representation coefficients of HSIs are learned by solving an optimization problem plugged with an image prior extracted from a neural denoising network. The proposed method is evaluated on simulated and real HSIs. An exhaustive array of experiments and comparisons with state-of-the-art denoisers were carried out.
KappaMask: AI-Based Cloudmask Processor for Sentinel-2
Authors: Domnich Marharyta , Sünter Indrek , Trofimov Heido , Wold Olga , Harun Fariha , Kostiukhin Anton , Järveoja Mihkel , Veske Mihkel , Tamm Tanel , Voormansik Kaupo , Olesk Aire , Boccia Valentina , Longepe Nicolas , Cadau Enrico Giuseppe
Published: October 2021

The Copernicus Sentinel-2 mission operated by the European Space Agency (ESA) provides comprehensive and continuous multi-spectral observations of all the Earth’s land surface since mid-2015. Clouds and cloud shadows significantly decrease the usability of optical satellite data, especially in agricultural applications; therefore, an accurate and reliable cloud mask is mandatory for effective EO optical data exploitation. During the last few years, image segmentation techniques have developed rapidly with the exploitation of neural network capabilities. With this perspective, the KappaMask processor using U-Net architecture was developed with the ability to generate a classification mask over northern latitudes into the following classes: clear, cloud shadow, semi-transparent cloud (thin clouds), cloud and invalid. For training, a Sentinel-2 dataset covering the Northern European terrestrial area was labelled. KappaMask provides a 10 m classification mask for Sentinel-2 Level-2A (L2A) and Level-1C (L1C) products. The total dice coefficient on the test dataset, which was not seen by the model at any stage, was 80% for KappaMask L2A and 76% for KappaMask L1C for clear, cloud shadow, semi-transparent and cloud classes. A comparison with rule-based cloud mask methods was then performed on the same test dataset, where Sen2Cor reached 59% dice coefficient for clear, cloud shadow, semi-transparent and cloud classes, Fmask reached 61% for clear, cloud shadow and cloud classes and Maja reached 51% for clear and cloud classes. The closest machine learning open-source cloud classification mask, S2cloudless, had a 63% dice coefficient providing only cloud and clear classes, while KappaMask L2A, with a more complex classification schema, outperformed S2cloudless by 17%.
Archetypal Analysis and Structured Sparse Representation for Hyperspectral Anomaly Detection
Authors: Zhao Genping , Li Fei , Zhang Xiuwei , Laakso Kati , Chan Jonathan Cheung-Wai
Published: October 2021

Hyperspectral images (HSIs) often contain pixels with mixed spectra, which makes it difficult to accurately separate the background signal from the anomaly target signal. To mitigate this problem, we present a method that applies spectral unmixing and structure sparse representation to accurately extract the pure background features and to establish a structured sparse representation model at a sub-pixel level by using the Archetypal Analysis (AA) scheme. Specifically, spectral unmixing with AA is used to unmix the spectral data to obtain representative background endmember signatures. Moreover the unmixing reconstruction error is utilized for the identification of the target. Structured sparse representation is also adopted for anomaly target detection by using the background endmember features from AA unmixing. Moreover, both the AA unmixing reconstruction error and the structured sparse representation reconstruction error are integrated together to enhance the anomaly target detection performance. The proposed method exploits background features at a sub-pixel level to improve the accuracy of anomaly target detection. Comparative experiments and analysis on public hyperspectral datasets show that the proposed algorithm potentially surpasses all the counterpart methods in anomaly target detection.
Determining Actual Evapotranspiration Based on Machine Learning and Sinusoidal Approaches Applied to Thermal High-Resolution Remote Sensing Imagery in a Semi-Arid Ecosystem
Authors: Reyes Rojas Luis A. , Moletto-Lobos Italo , Corradini Fabio , Mattar Cristian , Fuster Rodrigo , Escobar-Avaria Cristián
Published: October 2021

Evapotranspiration (ET) is key to assess crop water balance and optimize water-use efficiency. To attain sustainability in cropping systems, especially in semi-arid ecosystems, it is necessary to improve methodologies of ET estimation. A method to predict ET is by using land surface temperature (LST) from remote sensing data and applying the Operational Simplified Surface Energy Balance Model (SSEBop). However, to date, LST information from Landsat-8 Thermal Infrared Sensor (TIRS) has a coarser resolution (100 m) and longer revisit time than Sentinel-2, which does not have a thermal infrared sensor, which compromises its use in ET models as SSEBop. Therefore, in the present study we set out to use Sentinel-2 data at a higher spatial-temporal resolution (10 m) to predict ET. Three models were trained using TIRS’ images as training data (100 m) and later used to predict LST at 10 m in the western section of the Copiapó Valley (Chile). The models were built on cubist (Cub) and random forest (RF) algorithms, and a sinusoidal model (Sin). The predicted LSTs were compared with three meteorological stations located in olives, vineyards, and pomegranate orchards. RMSE values for the prediction of LST at 10 m were 7.09 K, 3.91 K, and 3.4 K in Cub, RF, and Sin, respectively. ET estimation from LST in spatial-temporal relation showed that RF was the best overall performance (R2 = 0.710) when contrasted with Landsat, followed by the Sin model (R2 = 0.707). Nonetheless, the Sin model had the lowest RMSE (0.45 mm d−1) and showed the best performance at predicting orchards’ ET. In our discussion, we argue that a simplistic sinusoidal model built on NDVI presents advantages over RF and Cub, which are constrained to the spatial relation of predictors at different study areas. Our study shows how it is possible to downscale Landsat-8 TIRS’ images from 100 m to 10 m to predict ET.
IEyeGASE: An Intelligent Eye Gaze-Based Assessment System for Deeper Insights into Learner Performance
Authors: Ramachandra Chandrika Kamath , Joseph Amudha
Published: October 2021

In the current education environment, learning takes place outside the physical classroom, and tutors need to determine whether learners are absorbing the content delivered to them. Online assessment has become a viable option for tutors to establish the achievement of course learning outcomes by learners. It provides real-time progress and immediate results; however, it has challenges in quantifying learner aspects like wavering behavior, confidence level, knowledge acquired, quickness in completing the task, task engagement, inattentional blindness to critical information, etc. An intelligent eye gaze-based assessment system called IEyeGASE is developed to measure insights into these behavioral aspects of learners. The system can be integrated into the existing online assessment system and help tutors re-calibrate learning goals and provide necessary corrective actions.
Technical Proposal for Monitoring Thermal and Mechanical Stresses of a Runway Pavement
Authors: Bruno Salvatore , Del Serrone Giulia , Di Mascio Paola , Loprencipe Giuseppe , Ricci Eugenio , Moretti Laura
Published: October 2021

Airport pavements should ensure regular and safe movements during their service life; the management body has to monitor the functional and structural characteristics, and schedule maintenance work, balancing the often conflicting goals of safety, economic and technical issues. This paper presents a remote monitoring system to evaluate the structural performance of a runway composed of concrete thresholds and a flexible central runway. Thermometers, strain gauges, and pressure cells will be embedded at different depths to continuously monitor the pavement’s response to traffic and environmental loads. An innovative system allows data acquisition and processing with specific calculation models, in order to inform the infrastructure manager, in real time, about the actual conditions of the pavement. In this way, the authors aim to develop a system that provides useful information for the correct implementation of an airport pavement management system (APMS) based on real-life data. Indeed, it permits comprehensive monitoring functions to be performed, based on the embedded sensing network.
Wavelet Analysis and Self-Similarity of Photoplethysmography Signals for HRV Estimation and Quality Assessment
Authors: Neshitov Alexander , Tyapochkin Konstantin , Smorodnikova Evgeniya , Pravdin Pavel
Published: October 2021

Peak-to-peak intervals in Photoplethysmography (PPG) can be used for heart rate variability (HRV) estimation if the PPG is collected from a healthy person at rest. Many factors, such as a person’s movements or hardware issues, can affect the signal quality and make some parts of the PPG signal unsuitable for reliable peak detection. Therefore, a robust HRV estimation algorithm should not only detect peaks, but also identify corrupted signal parts. We introduce such an algorithm in this paper. It uses continuous wavelet transform (CWT) for peak detection and a combination of features derived from CWT and metrics based on PPG signals’ self-similarity to identify corrupted parts. We tested the algorithm on three different datasets: a newly introduced Welltory-PPG-dataset containing PPG signals collected with smartphones using the Welltory app, and two publicly available PPG datasets: TROIKAand PPG-DaLiA. The algorithm demonstrated good accuracy in peak-to-peak intervals detection and HRV metric estimation.