bluuebunny/crossref_metadata_2025 huggingface dataset:
Most Effective Combination of Nutraceuticals for Improved Memory and Cognitive Performance in the House Cricket, Acheta domesticus
Authors: Madireddy Samskruthi , Madireddy Sahithi
Published: January 2021

Background: Dietary intake of multivitamins, zinc, polyphenols, omega fatty acids, and probiotics have all shown benefits in learning, spatial memory, and cognitive function. It is important to determine the most effective combination of antioxidants and/or probiotics because regular ingestion of all nutraceuticals may not be practical. This study examined various combinations of nutrients to determine which may best enhance spatial memory and cognitive performance in the house cricket (Acheta domesticus (L.)). Methods: Based on the 31 possible combinations of multivitamins, zinc, polyphenols, omega-3 polyunsaturated fatty acids (PUFAs), and probiotics, 128 house crickets were divided into one control group and 31 experimental groups with four house crickets in each group. Over eight weeks, crickets were fed their respective nutrients, and an Alternation Test and Recognition Memory Test were conducted every week using a Y-maze to test spatial working memory. Results: The highest-scoring diets shared by both tests were the combination of multivitamins, zinc, and omega-3 fatty acids (VitZncPuf; Alternation: slope = 0.07226, Recognition Memory: slope = 0.07001), the combination of probiotics, polyphenols, multivitamins, zinc, and omega-3 PUFAs (ProPolVitZncPuf; Alternation: slope = 0.07182, Recognition Memory: slope = 0.07001), the combination of probiotics, multivitamins, zinc, and omega-3 PUFAs (ProVitZncPuf; Alternation: slope = 0.06999, Recognition Memory: slope = 0.07001), and the combination of polyphenols, multivitamins, zinc, and omega-3 PUFAs (PolVitZncPuf; Alternation: slope = 0.06873, Recognition Memory: slope = 0.06956). Conclusion: All of the nutrient combinations demonstrated a benefit over the control diet, but the most significant improvement compared to the control was found in the VitZncPuf, ProVitZncPuf, PolVitZncPuf, and ProPolVitZncPuf. Since this study found no significant difference between the performance and improvement of subjects within these four groups, the combination of multivitamins, zinc, and omega-3 fatty acids (VitZncPuf) was concluded to be the most effective option for improving memory and cognitive performance.
SARS-CoV-2: Outline, Prevention, and Decontamination
Authors: Janik Edyta , Bartos Maciej , Niemcewicz Marcin , Gorniak Leslaw , Bijak Michal
Published: January 2021

The new coronavirus began to spread around the world in late 2019. Initially, it was found only in China, but in the following days there were reported cases of infections in other countries. Subsequently, based on taxonomy, phylogeny, and accepted practice, the virus was officially designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As a result of the rapid spread of SARS-CoV-2 in different countries around the world, on March 11, 2020, the World Health Organization (WHO) announced a status change in the disease caused by this coronavirus—from an epidemic to a pandemic disease. Although the world is taking unprecedented efforts to control the spread of SARS-CoV-2, the number of confirmed cases is rising. Therefore, effective preventive measures are needed in order to limit the spread of illness. The prevention measures are mainly based on information on the virus transmission routes, its environmental stability, and persistence on commonly touched surfaces. Social distancing, mask usage, and good hygiene practice are the most important recommendations for general public. Healthcare professionals who are directly involved in SARS-CoV-2 patients care are more exposed to virus infection and additional protection measures are necessary, including protective suits, aprons, face shields, goggles, and gloves. Due to the stability of SARS-CoV-2 on different surfaces, such as glass, paper, or wood, proper disinfection is crucial. Several studies have shown that despite the virus’s stability, it is sensitive to various disinfectants, such as ethanol, isopropanol, sodium hypochlorite, or hydrogen peroxide. These findings underline the importance of having comprehensive knowledge about SARS-CoV-2 and multidirectional strategies in order to limit the spread of the virus. This review is a summary of the most important information about SARS-CoV-2, such as its stability on different surfaces, protection strategies, and decontamination options.
An Unusual Case of Mixed Respiratory Capillariosis in a Dog
Authors: Morelli Simone , Marruchella Giuseppe , Passarelli Alessandra , Diakou Anastasia , Di Cesare Angela , Colombo Mariasole , Frangipane di Regalbono Antonio , Frate Alessandro , Traversa Donato
Published: January 2021

Nematodes belonging to the genus Capillaria infect a range of domestic and wild animals. Capillaria aerophila and Capillaria boehmi cause respiratory parasitoses in dogs and wild carnivores, e.g., foxes and mustelids, although they are often overlooked in canine clinical practice. The present report describes an unusual case of a severe and mixed infection by C. aerophila and C. boehmi in a privately housed dog that showed acute and life-threatening respiratory and neurological signs. Clinic-pathologic and epizootiological implications are described and discussed.
Predictive and Prognostic Utility of the Serum Level of Resistin-Like Molecule Beta for Risk Stratification in Patients with Community-Acquired Pneumonia
Authors: Chen Li , Luo Qiongzhen , Shang Ying , He Xinwei , Xu Yu , Gao Zhancheng
Published: January 2021

Despite progress in intensive care, the morbidity and mortality of patients with community-acquired pneumonia (CAP) remains high. Furthermore, the predictive and prognostic utility of resistin-like molecule beta (RELM-β) in patients with CAP is uncertain. This study investigated the role of RELM-β in patients with CAP and evaluated its correlation with disease severity and the risk of death. A prospective, multicenter study was conducted in 2017, and admission serum levels of RELM-β were detected using quantitative enzyme-linked immunosorbent assay. A total of 114 and 112 patients with severe CAP (SCAP) and non-severe CAP (NSCAP) were enrolled, respectively, with 15 healthy controls. Patients with SCAP, especially non-survivors, had significantly higher levels of serum RELM-β than patients with NSCAP. RELM-β levels positively correlated with severity scores and consistently predicted SCAP in patients with CAP (area under the curve = 0.794). Increased levels of RELM-β were closely related to the severity and prognosis of patients with CAP. The accuracy of 30-day mortality predictions of CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥ 65 years) can be significantly improved when combined with RELM-β levels. The level of RELM-β can assist clinicians in risk stratification of patients with CAP in early stages.
Synthesis and Anticancer Activity of Hybrid Molecules Based on Lithocholic and (5Z,9Z)-Tetradeca-5,9-dienedioic Acids Linked via Mono(di,tri,tetra)ethylene Glycol and α,ω-Diaminoalkane Units
Authors: D’yakonov Vladimir A. , Tuktarova Regina A. , Dzhemileva Lilya U. , Ishmukhametova Svetlana R. , Dzhemilev Usein M.
Published: January 2021

For the first time, hybrid molecules were synthesized on the basis of lithocholic and (5Z,9Z)-1,14-tetradeca-5,9-dienedicarboxylic acids, obtained in two stages using the homo-cyclomagnesiation reaction of 2-(hepta-5,6-diene-1-yloxy)tetrahydro-2H-pyran at the key stage. The resulting hybrid molecules containing 5Z,9Z-dienoic acids are of interest as novel synthetic biologically active precursors to create modern drugs for the treatment of human oncological diseases. The synthesized hybrid molecules were found to exhibit extremely high in vitro inhibitory activity against human topoisomerase I, which is 2–4 times higher than that of camptothecin, a known topoisomerase I inhibitor. Using flow cytometry and fluorescence microscopy, it was first shown that these new molecules are efficient apoptosis inducers in HeLa, U937, Jurkat, K562, and Hek293 cell cultures. In addition, the results of investigations into the effect of the synthesized acids on mitochondria and studies of possible DNA damage in Jurkat tumor cells are also presented.
(2-Aminobenzothiazole)-Methyl-1,1-Bisphosphonic Acids: Targeting Matrix Metalloproteinase 13 Inhibition to the Bone
Authors: Laghezza Antonio , Piemontese Luca , Brunetti Leonardo , Caradonna Alessia , Agamennone Mariangela , Loiodice Fulvio , Tortorella Paolo
Published: January 2021

Matrix Metalloproteinases (MMPs) are a family of secreted and membrane-bound enzymes, of which 24 isoforms are known in humans. These enzymes degrade the proteins of the extracellular matrix and play a role of utmost importance in the physiological remodeling of all tissues. However, certain MMPs, such as MMP-2, -9, and -13, can be overexpressed in pathological states, including cancer and metastasis. Consequently, the development of MMP inhibitors (MMPIs) has been explored for a long time as a strategy to prevent and hinder metastatic growth, but the important side effects linked to promiscuous inhibition of MMPs prevented the clinical use of MMPIs. Therefore, several strategies were proposed to improve the therapeutic profile of this pharmaceutical class, including improved selectivity toward specific MMP isoforms and targeting of specific organs and tissues. Combining both approaches, we conducted the synthesis and preliminary biological evaluation of a series of (2-aminobenzothiazole)-methyl-1,1-bisphosphonic acids active as selective inhibitors of MMP-13 via in vitro and in silico studies, which could prove useful for the treatment of bone metastases thanks to the bone-targeting capabilities granted by the bisphosphonic acid group.
Natural Marine and Terrestrial Compounds as Modulators of Matrix Metalloproteinases-2 (MMP-2) and MMP-9 in Alzheimer’s Disease
Authors: Ciccone Lidia , Vandooren Jennifer , Nencetti Susanna , Orlandini Elisabetta
Published: January 2021

Several studies have reported neuroprotective effects by natural products. A wide range of natural compounds have been investigated, and some of these may play a beneficial role in Alzheimer’s disease (AD) progression. Matrix metalloproteinases (MMPs), a family of zinc-dependent endopeptidases, have been implicated in AD. In particular, MMP-2 and MMP-9 are able to trigger several neuroinflammatory and neurodegenerative pathways. In this review, we summarize and discuss existing literature on natural marine and terrestrial compounds, as well as their ability to modulate MMP-2 and MMP-9, and we evaluate their potential as therapeutic compounds for neurodegenerative and neuroinflammatory diseases, with a focus on Alzheimer’s disease.
Effects of Selective Peroxisome Proliferator Activated Receptor Agonists on Corneal Epithelial Wound Healing
Authors: Tobita Yutaro , Arima Takeshi , Nakano Yuji , Uchiyama Masaaki , Shimizu Akira , Takahashi Hiroshi
Published: January 2021

The effects of each subtype-selective peroxisome proliferator activated receptor (PPAR) agonist (α, β/δ, γ) on corneal epithelial wound healing were investigated using a rat corneal alkali burn model. After the alkali burn, each PPAR agonist or vehicle ophthalmic solution was instilled topically onto the rat’s cornea. Corneal epithelial healing processes were evaluated by fluorescein staining. Pathological analyses and real-time reverse transcription polymerase chain reactions were performed to evaluate Ki67 (proliferative maker) expression and inflammatory findings. The area of the corneal epithelial defect at 12 h and 24 h after the alkali burn was significantly smaller in each PPAR group than in the vehicle group. Ki67 mRNA expression was increased in the PPARβ/δ group, whereas mRNA expressions of inflammatory cytokines were suppressed in all of the PPAR agonist groups. Nuclear factor kappa B (NF-κB) was the most suppressed in the PPARγ group. The accelerated corneal epithelial healing effects of each PPAR ligand were thought to be related to the promotion of proliferative capacity and inhibition of inflammation.
Determination of Inherent Dissolution Performance of Drug Substances
Authors: Sleziona Dominik , Mattusch Amelie , Schaldach Gerhard , Ely David R. , Sadowski Gabriele , Thommes Markus
Published: January 2021

The dissolution behavior of novel active pharmaceutical ingredients (API) is a crucial parameter in drug formulation since it frequently affects the drug release. Generally, a distinction is made between surface-reaction- and diffusion-controlled drug release. Therefore, dissolution studies such as the intrinsic dissolution test defined in the pharmacopeia have been performed for many years. In order to overcome the disadvantages of the common intrinsic dissolution test, a new experimental setup was developed within this study. Specifically, a flow channel was designed and tested for measuring the mass transfer from a flat, solid surface dissolving into a fluid flowing over the surface with well-defined flow conditions. A mathematical model was developed that distinguishes between surface-reaction- and diffusion-limited drug release based on experimental data. Three different drugs—benzocaine, theophylline and griseofulvin—were used to investigate the mass flux during dissolution due to surface reaction, diffusion and convection kinetics. This new technique shows potential to be a valuable tool for the identification of formulation strategies.
How Does the Addition of Kollidon®VA64 Inhibit the Recrystallization and Improve Ezetimibe Dissolution from Amorphous Solid Dispersions?
Authors: Szafraniec-Szczęsny Joanna , Antosik-Rogóż Agata , Kurek Mateusz , Gawlak Karolina , Górska Anna , Peralta Sebastian , Knapik-Kowalczuk Justyna , Kramarczyk Daniel , Paluch Marian , Jachowicz Renata
Published: January 2021

Amorphization serves as a strategy for the improvement of poor dissolution characteristics of many drug compounds. However, in many formulations the content of polymeric stabilizer is high, which is undesirable from the perspective of future applications. Thus, studying the composition-dependent stability of amorphous solid dispersions seems to be demanded. In this paper, we describe the amorphization of ezetimibe, a lipid-lowering drug, in the spray drying process and investigate the effect of polyvinylpyrrolidone-co-poly(vinyl acetate) (PVP/VA) content on the physical stability and dissolution characteristics of the drug. Fully amorphous systems were obtained when the concentration of the polymer in solid dispersion was as low as 20%. The amorphization led to the dissolution enhancement by even 70%, with a noticeable sudden increase at around 40% of PVP/VA content and very small variations for systems having 66–90% PVP/VA. It was also correlated to wettability characteristics of solid dispersions, which may suggest that in the vicinity of 40% of the polymer content, the behavior of the system becomes independent of the PVP/VA content.
Amoxicillin and Clarithromycin Mucoadhesive Delivery System for Helicobacter pylori Infection in a Mouse Model: Characterization, Pharmacokinetics, and Efficacy
Authors: Villegas Isabel , Rosillo María Ángeles , Alarcón-de-la-Lastra Catalina , Vázquez-Román Victoria , Llorente Maria , Sánchez Susana , Gil Ana Gloria , Alcalde Pilar , González Esther , Rosell Elisabet , Nieto Carles , Fernandez-Campos Francisco
Published: January 2021

Helicobacter pylori is the main pathogen responsible for gastric ulcers and a predisposing factor of stomach cancer. Although current treatment is usually successful, it requires high doses and frequent administration. An innovative mucoadhesive system (Mucolast®) loaded with amoxicillin and clarithromycin is proposed to improve the efficacy of treatment against H. pylori. The drug product was optimized based on its viscoelastic properties to obtain long-term stability of the vehicle. The drug release mechanisms were different for both antibiotics based on their solubilization status. A systemic and stomach pharmacokinetic profile was obtained after three different doses were administered to mice, obtaining similar systemic exposure levels but an increase in drug concentration in the stomach. The efficacy results in mice infected with H. pylori also demonstrated the superiority of the antibiotics when administered in Mucolast®, as shown by the bacterial count in stomach tissue and under histopathological and biochemical evaluation. The proposed treatment was efficacious and safe and is presented as a realistic alternative to current treatment options to improve patient compliance and to reduce bacterial resistance.
Additive Manufacturing of Oral Tablets: Technologies, Materials and Printed Tablets
Authors: Abaci Alperen , Gedeon Christina , Kuna Anna , Guvendiren Murat
Published: January 2021

Additive manufacturing (AM), also known as three-dimensional (3D) printing, enables fabrication of custom-designed and personalized 3D constructs with high complexity in shape and composition. AM has a strong potential to fabricate oral tablets with enhanced customization and complexity as compared to tablets manufactured using conventional approaches. Despite these advantages, AM has not yet become the mainstream manufacturing approach for fabrication of oral solid dosage forms mainly due to limitations of AM technologies and lack of diverse printable drug formulations. In this review, AM of oral tablets are summarized with respect to AM technology. A detailed review of AM methods and materials used for the AM of oral tablets is presented. This article also reviews the challenges in AM of pharmaceutical formulations and potential strategies to overcome these challenges.
Investigation of the Cellular Effects of Beta- Cyclodextrin Derivatives on Caco-2 Intestinal Epithelial Cells
Authors: Rusznyák Ágnes , Malanga Milo , Fenyvesi Éva , Szente Lajos , Váradi Judit , Bácskay Ildikó , Vecsernyés Miklós , Vasvári Gábor , Haimhoffer Ádám , Fehér Pálma , Ujhelyi Zoltán , Nagy Jr. Béla , Fejes Zsolt , Fenyvesi Ferenc
Published: January 2021

Cyclodextrins are widely used excipients for increasing water-solubility, delivery and bioavailability of lipophilic drugs. By using fluorescent cyclodextrin derivatives, we showed previously that cyclodextrins are able to enter Caco-2 intestinal cells by endocytosis, but the influence of different fluorescent labeling on the same cyclodextrin derivative has not been studied. The consequences of the cellular internalization of cyclodextrins have not been revealed yet either. The aims of this study were to compare the cellular internalization of fluorescein- and rhodamine-labeled (2-hydroxypropyl)-, (HPBCD) and randommethyl-β-cyclodextrins (RAMEB) and to investigate the intracellular effects of these derivatives on Caco-2 cells. Stimulation of the NF-kappa B pathway and autophagy and localization of these derivatives in lysosomes were tested. The endocytosis of these derivatives was examined by fluorescence microscopy and flow cytometry. Both fluorescein- and rhodamine-labeled derivatives entered the cells, therefore the type of the fluorescent labeling did not influence their internalization. Cyclodextrin pretreatment did not activate the translocation of the p65 subunit of the NF-kappa B heterodimer into the cell nuclei from the cytoplasm. After HPBCD or RAMEB treatment, formation of the autophagosomes did not increase compared to the control sample and at the same time these derivatives could be detected in lysosomes after internalization.
Effect of Si Doping on the Performance of GaN Schottky Barrier Ultraviolet Photodetector Grown on Si Substrate
Authors: Liang Fangzhou , Chen Wen , Feng Meixin , Huang Yingnan , Liu Jianxun , Sun Xiujian , Zhan Xiaoning , Sun Qian , Wu Qibao , Yang Hui
Published: January 2021

GaN Schottky barrier ultraviolet photodetectors with unintentionally doped GaN and lightly Si-doped n−-GaN absorption layers were successfully fabricated, respectively. The high-quality GaN films on the Si substrate both have a fairly low dislocation density and point defect concentration. More importantly, the effect of Si doping on the performance of the GaN-on-Si Schottky barrier ultraviolet photodetector was studied. It was found that light Si doping in the absorption layer can significantly increase the responsivity under reverse bias, which might be attributed to the persistent photoconductivity that originates from the lowering of the Schottky barrier height. In addition, the devices with unintentionally doped GaN demonstrated a relatively high-speed photo response. We briefly studied the mechanism of changes in Schottky barrier, dark current and the characteristic of response time.
Plants of the Spontaneous Flora with Beneficial Action in the Management of Diabetes, Hepatic Disorders, and Cardiovascular Disease
Authors: Ignat Maria Valentina , Coldea Teodora Emilia , Salanță Liana Claudia , Mudura Elena
Published: January 2021

The current pharmacological agents advised for the management of diabetes as well as cardiovascular and hepatic diseases are subject to numerous studies for safety and efficacy. Therefore, it is worth looking into alternative therapeutic aids such as natural products of medicinal plants. By a broad review of in vitro and in vivo studies on the various dandelion, chicory, and mulberry extracts, this work highlights their bioactive compounds and therapeutic action when used as a prevention and management aid in public health such as diabetes, cardiovascular disease, and hepatic disorders like non-alcoholic steatohepatitis. Natural products of dandelion leaves and root extracts can suppress the development of liver cancer, decrease insulin resistance, and suppress total triglyceride and cholesterol levels. Recent studies on mulberry leaves extracts indicated that they could decrease palmitic acid-induced lipotoxicity, increase total cholesterol and bile acid excretion, improve superoxide dismutase expression, and improve insulin resistance. Chicory root extracts boost satiety, reverse insulin resistance, and augment lipid metabolism thanks to their contents in chicoric acid, chlorogenic acid, and polysaccharides. Taraxacum officinale L., Morus nigra L., and Cichorium intybus L. present hepatoprotective, anti-inflammatory, antioxidant, hypolipidemic, and hypoglycemic activities and are shown to be advantageous in the management of obesity, dyslipidemia, Type 2 diabetes, and non-alcoholic fatty liver diseases. These plants are commonly available in the European spontaneous flora and more attention could be paid to their natural products.
Crude Citric Acid of Trichoderma asperellum: Tomato Growth Promotor and Suppressor of Fusarium oxysporum f. sp. lycopersici
Authors: Al-Askar Abdulaziz A. , Saber WesamEldin I. A. , Ghoneem Khalid M. , Hafez Elsayed E. , Ibrahim Amira A.
Published: January 2021

Presently, the bioprocessing of agricultural residues to various bioactive compounds is of great concern, with the potential to be used as plant growth promoters and as a reductive of various diseases. Lycopersiconesculentum, one of the most consumed crops in the human diet, is attacked by Fusarium wilt disease, so the main aim is to biocontrol the pathogen. Several fungal species were isolated from decayed maize stover (MS). Trichodermaasperellum was chosen based on its organic acid productivity and was molecularly identified (GenBank accession number is MW195019). Citric acid (CA) was the major detected organic acid by HPLC. In vitro, CA of T.asperellum at 75% completely repressed the growth of Fusariumoxysporum f. sp. lycopersici (FOL). In vivo, soaking tomato seeds in CA enhanced the seed germination and vigor index. T. asperellum and/or its CA suppressed the wilt disease caused by FOL compared to control. There was a proportional increment of plant growth and yield, as well as improvements in the biochemical parameters (chlorophyll pigments, total phenolic contents and peroxidase, and polyphenol oxidase activities), suggesting targeting both the bioconversion of MS into CA and biological control of FOL.
Acknowledgment to Reviewers of Plants in 2020
Authors:   Plants Editorial Office
Published: January 2021

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Plants maintains its standards for the high quality of its published papers [...]
Apple Fermented Products: An Overview of Technology, Properties and Health Effects
Authors: Guiné Raquel P. F. , Barroca Maria João , Coldea Teodora Emilia , Bartkiene Elena , Anjos Ofélia
Published: January 2021

As an easily adapted culture, with overloaded production in some parts of the globe, apples and their by-products are being redirected to pharmaceutical, canning and beverages industries, both alcoholic and non-alcoholic. Fermentation is generally considered to increase the bioavailability of bioactive compounds found in apple, by impacting, through a high degree of changes, the product’s properties, including composition and health-promoting attributes, as well as their sensory profile. Probiotic apple beverages and apple vinegar are generally considered as safe and healthy products by the consumers. Recently, contributions to human health, both in vivo and in vitro studies, of non-alcoholic fermented apple-based products have been described. This review highlighted the advances in the process optimization of apple-based products considering vinegar, cider, pomace, probiotic beverages and spirits’ technologies. The different processing impacts on physical-chemical, nutritional and sensory profiles of these products are also presented. Additionally, the harmful effects of toxic compounds and strategies to limit their content in cider and apple spirits are illustrated. New trends of fermented apple-based products applicability in tangential industries are summarized.
Acknowledgment to Reviewers of Recycling in 2020
Authors:   Recycling Editorial Office
Published: January 2021

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Recycling maintains its standards for the high quality of its published papers [...]
From Victim to Hangman? Ennahda, Salafism and the Tunisian Transition
Authors: Cavatorta Francesco , Torelli Stefano
Published: January 2021

The article revisits the notion of post-Islamism that Roy and Bayat put forth to investigate its usefulness in analysing the Tunisian party Ennahda and its role in the Tunisian transition. The article argues that the notion of post-Islamism does not fully capture the ideological and political evolution of Islamist parties, which, despite having abandoned their revolutionary ethos, still compete in the political arena through religious categories that subsume politics to Islam. It is only by taking seriously these religious categories that one can understand how Ennahda dealt with the challenge coming from Salafis.
Acknowledgment to Reviewers of Risks in 2020
Authors:   Risks Editorial Office
Published: January 2021

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Risks maintains its standards for the high quality of its published papers [...]
What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains
Authors: Kohv Keijo , Lukason Oliver
Published: January 2021

This paper aims to compare the accuracy of financial ratios, tax arrears and annual report submission delays for the prediction of bank loan defaults. To achieve this, 12 variables from these three domains are used, while the study applies a longitudinal whole-population dataset from an Estonian commercial bank with 12,901 observations of defaulted and non-defaulted firms. The analysis is performed using statistical (logistic regression) and machine learning (neural networks) methods. Out of the three domains used, tax arrears show high prediction capabilities for bank loan defaults, while financial ratios and reporting delays are individually not useful for that purpose. The best default prediction accuracies were 83.5% with tax arrears only and 89.1% with all variables combined. The study contributes to the extant literature by enhancing the bank loan default prediction accuracy with the introduction of novel variables based on tax arrears, and also by indicating the pecking order of satisfying creditors’ claims in the firm failure process.
Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique
Authors: Guo Jinyun , Hou Rui , Zhou Maosheng , Jin Xin , Li Chengming , Liu Xin , Gao Hao
Published: January 2021

From late 2019 to early 2020, forest fires in southeastern Australia caused huge economic losses and huge environmental pollution. Monitoring forest fires has become increasingly important. A new method of fire detection using the difference between global navigation satellite system (GNSS)-derived precipitable water vapor and radiosonde-derived precipitable water vapor (ΔPWV) is proposed. To study the feasibility of the new method, the relationship is studied between particulate matter 10 (PM10) (2.5 to 10 microns particulate matter) and ΔPWV based on Global Positioning System (GPS) data, radiosonde data, and PM10 data from 1 June 2019 to 1 June 2020 in southeastern Australia. The results show that before the forest fire, ΔPWV and PM10 were smaller and less fluctuating. When the forest fire happened, ΔPWV and PM10 were increasing. Then after the forest fire, PM10 became small with relatively smooth fluctuations, but ΔPWV was larger and more fluctuating. Correlation between the 15-day moving standard deviation (STD) time series of ΔPWV and PM10 after the fire was significantly higher than that before the fire. This study shows that ΔPWV is effective in monitoring forest fires based on GNSS technique before and during forest fires in climates with more uniform precipitation, and using ΔPWV to detect forest fires based on GNSS needs to be further investigated in climates with more precipitation and severe climate change.
The Symmetry of GPS Orbit Ascending Nodes
Authors: Dabrowski Pawel S.
Published: January 2021

Theoretical nominal GPS orbits are parallel and share six ascending nodes of orbital planes. However, due to the perturbations and continuous modernization of the system, this state does not occur. The configuration of satellite orbits is continuously monitored by the control segment and presented regularly in the form of a GPS almanac. Almanacs, however, do not contain a parameter defining the convergence of orbits. This work presents a novel method of assessment of the configuration of orbit ascending nodes compared with the nominal constellation state. The method is a tool for space segment monitoring and detection of anomalies. The source data were 7035 System Effectiveness Model almanacs published from the 847th to 2123rd GPS weeks (March 1996–September 2020). The algorithm uses the procedure of assigning satellites to orbital planes and both the robust estimation and the least-squares methods to determine the estimates of the angular separation of orbit ascending nodes. A long-term analysis of the symmetry and trend of changes in the position of the ascending nodes was conducted. The study showed the occurrence of significant anomalies. The research provides information on the trend of satellite orbit separations and deviations of orbital planes from the initial hexagonal GPS symmetry.
Towards Semantic SLAM: 3D Position and Velocity Estimation by Fusing Image Semantic Information with Camera Motion Parameters for Traffic Scene Analysis
Authors: Mansour Mostafa , Davidson Pavel , Stepanov Oleg , Piché Robert
Published: January 2021

In this paper, an EKF (Extended Kalman Filter)-based algorithm is proposed to estimate 3D position and velocity components of different cars in a scene by fusing the semantic information and car model, extracted from successive frames with camera motion parameters. First, a 2D virtual image of the scene is made using a prior knowledge of the 3D Computer Aided Design (CAD) models of the detected cars and their predicted positions. Then, a discrepancy, i.e., distance, between the actual image and the virtual image is calculated. The 3D position and the velocity components are recursively estimated by minimizing the discrepancy using EKF. The experiments on the KiTTi dataset show a good performance of the proposed algorithm with a position estimation error up to 3–5% at 30 m and velocity estimation error up to 1 m/s.
Crop Height Estimation of Corn from Multi-Year RADARSAT-2 Polarimetric Observables Using Machine Learning
Authors: Xie Qinghua , Wang Jinfei , Lopez-Sanchez Juan , Peng Xing , Liao Chunhua , Shang Jiali , Zhu Jianjun , Fu Haiqiang , Ballester-Berman J.
Published: January 2021

This study presents a demonstration of the applicability of machine learning techniques for the retrieval of crop height in corn fields using space-borne PolSAR (Polarimetric Synthetic Aperture Radar) data. Multi-year RADARSAT-2 C-band data acquired over agricultural areas in Canada, covering the whole corn growing period, are exploited. Two popular machine learning regression methods, i.e., Random Forest Regression (RFR) and Support Vector Regression (SVR) are adopted and evaluated. A set of 27 representative polarimetric parameters are extracted from the PolSAR data and used as input features in the regression models for height estimation. Furthermore, based on the unique capability of the RFR method to determine variable importance contributing to the regression, a smaller number of polarimetric features (6 out of 27 in our study) are selected in the final regression models. Results of our study demonstrate that PolSAR observables can produce corn height estimates with root mean square error (RMSE) around 40–50 cm throughout the growth cycle. The RFR approach shows better overall accuracy in corn height estimation than the SVR method in all tests. The six selected polarimetric features by variable importance ranking can generate better results. This study provides a new perspective on the use of PolSAR data in retrieving agricultural crop height from space.
The Application of Terrestrial LiDAR for Geohazard Mapping, Monitoring and Modelling in the British Geological Survey
Authors: Jones Lee , Hobbs Peter
Published: January 2021

Geomatics is the discipline of electronically gathering, storing, processing, and delivering spatially related digital information; it continues to be one of the fastest expanding global markets, driven by technology. The British Geological Survey (BGS) geomatics capabilities have been utilized in a variety of scientific studies such as the monitoring of actively growing volcanic lava domes and rapidly retreating glaciers; coastal erosion and platform evolution; inland and coastal landslide modelling; mapping of geological structures and fault boundaries; rock stability and subsidence feature analysis, and geo-conservation. In 2000, the BGS became the first organization outside the mining industry to use Terrestrial LiDAR Scanning (TLS) as a tool for measuring change; paired with a Global Navigation Satellite System (GNSS), BGS were able to measure, monitor, and model geomorphological features of landslides in the United Kingdom (UK) digitally. Many technologies are used by the BGS to monitor the earth, employed on satellites, airplanes, drones, and ground-based equipment, in both research and commercial settings to carry out mapping, monitoring, and modelling of earth surfaces and processes. Outside BGS, these technologies are used for close-range, high-accuracy applications such as bridge and dam monitoring, crime and accident scene analysis, forest canopy and biomass measurements and military applications.
Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images
Authors: Fernández Claudio Ignacio , Haddadi Ata , Leblon Brigitte , Wang Jinfei , Wang Keri
Published: January 2021

Cucumber powdery mildew, which is caused by Podosphaera xanthii, is a major disease that has a significant economic impact in cucumber greenhouse production. It is necessary to develop a non-invasive fast detection system for that disease. Such a system will use multispectral imagery acquired at a close range with a camera attached to a mobile cart’s mechanic extension. This study evaluated three image registration methods applied to non-georeferenced multispectral images acquired at close range over greenhouse cucumber plants with a MicaSense® RedEdge camera. The detection of matching points was performed using Speeded-Up Robust Features (SURF), and outliers matching points were removed using the M-estimator Sample Consensus (MSAC) algorithm. Three geometric transformations (affine, similarity, and projective) were considered in the registration process. For each transformation, we mapped the matching points of the blue, green, red, and NIR band images into the red-edge band space and computed the root mean square error (RMSE in pixel) to estimate the accuracy of each image registration. Our results achieved an RMSE of less than 1 pixel with the similarity and affine transformations and of less than 2 pixels with the projective transformation, whatever the band image. We determined that the best image registration method corresponded to the affine transformation because the RMSE is less than 1 pixel and the RMSEs have a Gaussian distribution for all of the bands, but the blue band.
Design of a Didactical Activity for the Analysis of Uncertainties in Thermography through the Use of Robust Statistics as Teacher-Oriented Approach
Authors: Rodríguez-Gonzálvez Pablo , Rodríguez-Martín Manuel
Published: January 2021

The thermography as a methodology to quantitative data acquisition is not usually addressed in the degrees of university programs. The present manuscript proposes a novel approach for the acquisition of advanced competences in engineering courses associated with the use of thermographic images via free/open-source software solutions. This strategy is established from a research based on the statistical and three-dimensional visualization techniques over thermographic imagery to improve the interpretation and comprehension of the different sources of error affecting the measurements and, thereby, the conclusions and analysis arising from them. The novelty is focused on the detection of non-normalities in thermographic images, which is illustrates in the experimental section. Additionally, the specific workflow for the generation of learning material related with this aim is raised for asynchronous and e-learning programs. These virtual materials can be easily deployed in an institutional learning management system, allowing the students to work with the models by means of free/open-source solutions easily. Subsequently, the present approach will give new tools to improve the application of professional techniques, will improve the students’ critical sense to know how to interpret the uncertainties in thermography using a single thermographic image, therefore they will be better prepared to face future challenges with more critical thinking.
Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine
Authors: Pipia Luca , Amin Eatidal , Belda Santiago , Salinero-Delgado Matías , Verrelst Jochem
Published: January 2021

For the last decade, Gaussian process regression (GPR) proved to be a competitive machine learning regression algorithm for Earth observation applications, with attractive unique properties such as band relevance ranking and uncertainty estimates. More recently, GPR also proved to be a proficient time series processor to fill up gaps in optical imagery, typically due to cloud cover. This makes GPR perfectly suited for large-scale spatiotemporal processing of satellite imageries into cloud-free products of biophysical variables. With the advent of the Google Earth Engine (GEE) cloud platform, new opportunities emerged to process local-to-planetary scale satellite data using advanced machine learning techniques and convert them into gap-filled vegetation properties products. However, GPR is not yet part of the GEE ecosystem. To circumvent this limitation, this work proposes a general adaptation of GPR formulation to parallel processing framework and its integration into GEE. To demonstrate the functioning and utility of the developed workflow, a GPR model predicting green leaf area index (LAIG) from Sentinel-2 imagery was imported. Although by running this GPR model into GEE any corner of the world can be mapped into LAIG at a resolution of 20 m, here we show some demonstration cases over western Europe with zoom-ins over Spain. Thanks to the computational power of GEE, the mapping takes place on-the-fly. Additionally, a GPR-based gap filling strategy based on pre-optimized kernel hyperparameters is also put forward for the generation of multi-orbit cloud-free LAIG maps with an unprecedented level of detail, and the extraction of regularly-sampled LAIG time series at a pixel level. The ability to plugin a locally-trained GPR model into the GEE framework and its instant processing opens up a new paradigm of remote sensing image processing.
Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics
Authors: Hashimoto Kana , Shimozono Takenori , Matsuba Yoshinao , Okabe Takumi
Published: January 2021

Monitoring the morphological evolution of a river-mouth bar is of both practical and scientific importance. A large amount of sediment is transported from a river to surrounding littoral cells via a deltaic bar after an extreme weather event. However, it is often not feasible to capture drastic morphological changes in the short term with conventional bathymetric surveys. This paper presents a depth-inversion method based on unmanned aerial vehicle technology to estimate two-dimensional bathymetry from video-sensed swell propagation. The estimation algorithm is tested over four cases with varying wave and bathymetric conditions and is validated with transect survey data. The test results suggest that the method can estimate deltaic-bar topography in front of a river mouth with a root-mean-square error of <0.5 m. The applicable range is limited by wave breaking in the inner bar and up to a depth of ~8 m, where swell intensity signals become ambiguous. A comparison of the different cases shows that the method works better under calm weather conditions with dominant swells propagating from non-local sources. Significant morphological changes of a river-mouth bar due to a powerful typhoon are successfully detected by observations right before and after the event.
Continuous Multi-Angle Remote Sensing and Its Application in Urban Land Cover Classification
Authors: Yao Yuan , Leung Yee , Fung Tung , Shao Zhenfeng , Lu Jie , Meng Deyu , Ying Hanchi , Zhou Yu
Published: January 2021

Because of the limitations of hardware devices, such as the sensors, processing capacity, and high accuracy altitude control equipment, traditional optical remote sensing (RS) imageries capture information regarding the same scene from mostly one single angle or a very small number of angles. Nowadays, with video satellites coming into service, obtaining imageries of the same scene from a more-or-less continuous array of angles has become a reality. In this paper, we analyze the differences between the traditional RS data and continuous multi-angle remote sensing (CMARS) data, and unravel the characteristics of the CMARS data. We study the advantages of using CMARS data for classification and try to capitalize on the complementarity of multi-angle information and, at the same time, to reduce the embedded redundancy. Our arguments are substantiated by real-life experiments on the employment of CMARS data in order to classify urban land covers while using a support vector machine (SVM) classifier. They show the superiority of CMARS data over the traditional data for classification. The overall accuracy may increase up to about 9% with CMARS data. Furthermore, we investigate the advantages and disadvantages of directly using the CMARS data, and how such data can be better utilized through the extraction of key features that characterize the variations of spectral reflectance along the entire angular array. This research lay the foundation for the use of CMARS data in future research and applications.
A Review: Development of Computer Vision-Based Lameness Detection for Dairy Cows and Discussion of the Practical Applications
Authors: Kang Xi , Zhang Xu Dong , Liu Gang
Published: January 2021

The computer vision technique has been rapidly adopted in cow lameness detection research due to its noncontact characteristic and moderate price. This paper attempted to summarize the research progress of computer vision in the detection of lameness. Computer vision lameness detection systems are not popular on farms, and the accuracy and applicability still need to be improved. This paper discusses the problems and development prospects of this technique from three aspects: detection methods, verification methods and application implementation. The paper aims to provide the reader with a summary of the literature and the latest advances in the field of computer vision detection of lameness in dairy cows.
Single-Channel Multiple-Receiver Sound Source Localization System with Homomorphic Deconvolution and Linear Regression
Authors: Park Yeonseok , Choi Anthony , Kim Keonwook
Published: January 2021

The conventional sound source localization systems require the significant complexity because of multiple synchronized analog-to-digital conversion channels as well as the scalable algorithms. This paper proposes a single-channel sound localization system for transport with multiple receivers. The individual receivers are connected by the single analog microphone network which provides the superimposed signal over simple connectivity based on asynchronized analog circuit. The proposed system consists of two computational stages as homomorphic deconvolution and machine learning stage. A previous study has verified the performance of time-of-flight estimation by utilizing the non-parametric and parametric homomorphic deconvolution algorithms. This paper employs the linear regression with supervised learning for angle-of-arrival prediction. Among the circular configurations of receiver positions, the optimal location is selected for three-receiver structure based on the extensive simulations. The non-parametric method presents the consistent performance and Yule–Walker parametric algorithm indicates the least accuracy. The Steiglitz–McBride parametric algorithm delivers the best predictions with reduced model order as well as other parameter values. The experiments in the anechoic chamber demonstrate the accurate predictions in proper ensemble length and model order.