bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Light Intensity, Temperature, and Nutrients to Enhance the Bioactive Content of Hyperforin and Rutin in St. John’s Wort
Authors: Kuo Chia-Hung , Chou Yi-Chin , Liao Kuo-Chun , Shieh Chwen-Jen , Deng Tzu-Shing
Published: September 2020

St. John’s wort (Hypericum perforatum L.) is a medicinal plant that alleviates depression and other disorders due to its abundance of active ingredients. Hyperforin, rutin, and melatonin are the main active, and important, ingredients in St. John’s wort that alleviate depression. In order to investigate the optimal conditions for accumulating these active ingredients, design of experiments and response surface methodology (RSM) was employed in this study. Two-month-old St John’s wort plants were cultivated in growth chambers at varying temperatures, light intensities, and nutrient solution concentrations before analysis by HPLC, for determining differences in hyperforin, rutin, and melatonin content. The results showed that hyperforin and rutin contents were significantly influenced by temperature (18–23 °C) and light intensity (49–147 μmol m−2 s−1 photosynthetic photon flux density (PPFD)), whereas Hoagland’s nutrient solution concentration (25–75%) had little effect. The accumulation of melatonin might not be influenced by cultivation conditions. Light intensity and temperature are easily controlled environmental factors in artificial cultivation, both of which are related to secondary metabolite production in the plant. Based on RSM, the optimal conditions for the accumulation of hyperforin and rutin were obtained. The maximum content of hyperforin was 5.6 mg/g, obtained at a temperature of 19 °C, a nutrient solution concentration of 45%, and a light intensity of 49 μmol m−2 s−1 PPFD. The maximum content of rutin was 3.8 mg/g obtained at a temperature of 18 °C, a nutrient solution concentration of 50%, and a light intensity of 147 μmol m−2 s−1 PPFD. This evaluation of suitable conditions for the accumulation of bioactive compounds in St. John’s wort can be applied to plant factories on a large scale.
Experimental Research and Development on the Natural Convection of Suspensions of Nanoparticles—A Comprehensive Review
Authors: Murshed S. M. Sohel , Sharifpur Mohsen , Giwa Solomon , Meyer Josua P.
Published: September 2020

Suspensions of nanoparticles, widely known as nanofluids, are considered as advanced heat transfer media for thermal management and conversion systems. Research on their convective thermal transport is of paramount importance for their applications in such systems such as heat exchangers and solar collectors. This paper presents experimental research on the natural convection heat transfer performances of nanofluids in different geometries from thermal management and conversion perspectives. Experimental results and available experiment-derived correlations for the natural thermal convection of nanofluids are critically analyzed. Other features such as nanofluid preparation, stability evaluation and thermophysical properties of nanofluids that are important for this thermal transfer feature are also briefly reviewed and discussed. Additionally, techniques (active and passive) employed for enhancing the thermo-convection of nanofluids in different geometries are highlighted and discussed. Hybrid nanofluids are featured in this work as the newest class of nanofluids, with particular focuses on the thermophysical properties and natural convection heat transfer performance in enclosures. It is demonstrated that there has been a lack of accurate stability evaluation given the inconsistencies of available results on these properties and features of nanofluids. Although nanofluids exhibit enhanced thermophysical properties such as viscosity and thermal conductivity, convective heat transfer coefficients were observed to deteriorate in some cases when nanofluids were used, especially for nanoparticle concentrations of more than 0.1 vol.%. However, there are inconsistencies in the literature results, and the underlying mechanisms are also not yet well-understood despite their great importance for practical applications.
Functionalization of Molybdenum Disulfide via Plasma Treatment and 3-Mercaptopropionic Acid for Gas Sensors
Authors: Seo Won Seok , Kim Dae Ki , Han Ji-Hoon , Park Kang-Bak , Ryu Su Chak , Min Nam Ki , Kim Joon Hyub
Published: September 2020

Monolayer and multilayer molybdenum disulfide (MoS2) materials are semiconductors with direct/indirect bandgaps of 1.2–1.8 eV and are attractive due to their changes in response to electrical, physicochemical, biological, and mechanical factors. Since the desired electrical properties of MoS2 are known, research on its electrical properties has increased, with focus on the deposition and growth of large-area MoS2 and its functionalization. While research on the large-scale production of MoS2 is actively underway, there is a lack of studies on functionalization approaches, which are essential since functional groups can help to dissolve particles or provide adequate reactivity. Strategies for producing films of functionalized MoS2 are rare, and what methods do exist are either complex or inefficient. This work introduces an efficient way to functionalize MoS2. Functional groups are formed on the surface by exposing MoS2 with surface sulfur vacancies generated by plasma treatment to 3-mercaptopropionic acid. This technique can create 1.8 times as many carboxyl groups on the MoS2 surface compared with previously reported strategies. The MoS2-based gas sensor fabricated using the proposed method shows a 2.6 times higher sensitivity and much lower detection limit than the untreated device.
Relationship between Sleep and Hedonic Appetite in Shift Workers
Authors: Vidafar Parisa , Cain Sean W. , Shechter Ari
Published: September 2020

Short and/or poor sleep are established behavioral factors which can contribute to excess food intake, and emerging evidence suggests that disturbed circadian rhythms may also impact food intake regulation. Together, disturbed sleep and circadian rhythms may help explain the excess risk for obesity seen in shift workers. To date, however, the details of how shift work may impact food intake regulation are still not fully defined. Here we examined the relationship between sleep characteristics and hedonic control of appetite in shift workers. A total of 63 shift workers (mean (M) age: 36.7 years, standard deviation (SD): 12.0; 59% women) completed an online survey comprising self-reported measures of body weight regulation, sleep (Pittsburgh Sleep Quality Index, Sleep Hygiene Index), and hedonic control of appetite (Food Craving Inventory, Power of Food Scale). Seventy-one percent reported some weight change since starting shift work, and 84% of those reported weight gain (M = +11.3 kg, SD = 9.1). Worse sleep quality and shorter sleep duration were associated with more food cravings, and worse sleep quality and hygiene were associated with higher appetitive drive to consume palatable food (greater hedonic drive). This preliminary study suggests hedonic pathways are potentially contributing to weight gain in shift workers with disturbed sleep.
Association of Dietary Patterns with Metabolic Syndrome
Authors: Di Daniele Nicola
Published: September 2020

Metabolic syndrome (MetS), as originally defined by Jean Vague in 1940, was identified as a cluster of chronic, inflammatory pathologies, such as arterial hypertension, abdominal obesity, high glucose levels, high triglyceride levels and low HDL levels in the blood [...]
Consumers’ Fears Regarding Food Availability and Purchasing Behaviors during the COVID-19 Pandemic: The Importance of Trust and Perceived Stress
Authors: Jeżewska-Zychowicz Marzena , Plichta Marta , Królak Maria
Published: September 2020

The present study aimed to investigate whether trust in circulating information and perceived stress are predictors of consumers’ fear of limited access to food as well as predictors of food purchase behaviors during the COVID-19 pandemic. The computer-assisted web interviewing (CAWI) technique was used to collect data from 1033 Polish adults in March 2020. Logistic regression was used to estimate the likelihood of fear of limited access to food and the likelihood of purchase of larger amounts of food than usual. The likelihood of experiencing fear of limited access to food increased by 16% with higher perceived stress, by 50% with higher trust in “Mass media and friends”, and by 219% with perceived changes in food availability in the previous month. Trust in “Polish government institutions” decreased the chance of experiencing such fears by 22%. The likelihood of purchasing larger quantities of food than usual increased by 9% with higher perceived stress, by 46% with higher trust in “Mass media and friends”, by 81% with perceived changes in food availability in the last month, and by 130% with fears of limited access to food as the pandemic spreads. Government institutions may have difficulty in disseminating pandemic-related recommendations through media, not only due to relatively low trust people have in media organizations but also due to the increasing likelihood of the occurrence of both fears regarding food availability and panic-stricken food-buying behaviors with increase in trust in this source of information. Therefore, it is necessary to develop interventions that will reduce perceived stress and improve the trust in information from reputable sources.
Pathogenic Delivery: The Biological Roles of Cryptococcal Extracellular Vesicles
Authors: de Oliveira Haroldo C. , Castelli Rafael F. , Reis Flavia C. G. , Rizzo Juliana , Rodrigues Marcio L.
Published: September 2020

Extracellular vesicles (EVs) are produced by all domains of life. In fungi, these structures were first described in Cryptococcus neoformans and, since then, they were characterized in several pathogenic and non-pathogenic fungal species. Cryptococcal EVs participate in the export of virulence factors that directly impact the Cryptococcus–host interaction. Our knowledge of the biogenesis and pathogenic roles of Cryptococcus EVs is still limited, but recent methodological and scientific advances have improved our understanding of how cryptococcal EVs participate in both physiological and pathogenic events. In this review, we will discuss the importance of cryptococcal EVs, including early historical studies suggesting their existence in Cryptococcus, their putative mechanisms of biogenesis, methods of isolation, and possible roles in the interaction with host cells.
Hybrid Multimodal Imaging Synthons for Chemoselective and Efficient Biomolecule Modification with Chelator and Near-Infrared Fluorescent Cyanine Dye
Authors: Hübner Ralph , von Kiedrowski Valeska , Benkert Vanessa , Wängler Björn , Schirrmacher Ralf , Krämer Roland , Wängler Carmen
Published: September 2020

The development of hybrid multimodal imaging synthons (MIS), carrying in addition to a chelator for radiometal labeling also a near-infrared (NIR) fluorescent cyanine dye was the aim of this work. The MIS should be introducible into biomolecules of choice via an efficient and chemoselective click chemistry reaction. After chemical optimization, a successful synthetic strategy towards such hybrid MIS was developed, based on solid phase-based synthesis techniques and applying different near-infrared fluorescent cyanine dyes. The developed hybrid agents were shown to be easily introducible into a model homobivalent peptidic gastrin-releasing peptide receptor- (GRPR)-specific carrier without forming any side products and the MIS as well as their bioconjugates were radiolabeled with the positron-emitter 68Ga3+. The hybrid multimodal agents were characterized with regard to their logDs, GRPR target affinities and photophysical characteristics. It could be shown that the properties of the bioconjugates were not per se affected by the introduction of the MIS but that the cyanine dye used and specifically the number of comprised negative charges per dye molecule can have a considerable influence on target receptor binding. Thus, the molecular toolbox described here enables the synthesis of tailored hybrid multimodal imaging synthons for biomolecule modification, meeting the specific need and envisioned application of the combined imaging agent.
Potential for Detection of Safety Signals for Over-the-Counter Medicines Using National ADR Spontaneous Reporting Data: The Example of OTC NSAID-Associated Gastrointestinal Bleeding
Authors: Amatya Elina , Fois Romano , Williams Kylie A. , Pont Lisa G.
Published: September 2020

One post-marketing surveillance challenge for many regulatory authorities is access to information regarding the safety of over-the-counter (OTC) medicines. National spontaneous adverse drug reaction (ADR) report data represent a rich potential data source for the detection of safety signals associated with OTC medicines, yet little is known regarding the possibility of detecting safety signals for OTC medicines within these datasets. The aim of this study was to evaluate the potential for detecting safety signals for OTC medicines in National ADR spontaneous reporting data, using OTC non-steroidal anti-inflammatory drugs (NSAIDs) and gastrointestinal bleeding as an example. Data from the Australian Adverse Drug Reactions System (ADRS) dataset (1971–2008) and the Canadian Vigilance Adverse Reaction Online Database (VAROD) (1965–2013) were used to explore the feasibility of using spontaneous reporting data, exploring the association between gastrointestinal bleeding and the use of OTC NSAIDs. Safety signals were examined using disproportionality analyses and reporting odds ratios calculated. After adjusting for age, gender, medications known to increase the risk of bleeding, and medications used for the management of conditions associated with an increased risk of bleeding, a two-fold increase in the risk of gastrointestinal (GI) bleeding with OTC NSAID was observed within each dataset. This study demonstrates that spontaneous ADR reporting data can be used in pharmacovigilance to monitor the safety of OTC medicines.
Soil Organic Matter Degradation in Long-Term Maize Cultivation and Insufficient Organic Fertilization
Authors: Balík Jiří , Kulhánek Martin , Černý Jindřich , Sedlář Ondřej , Suran Pavel
Published: September 2020

Soil organic matter carbon (CSOM) compounds degradation was observed in long-term field experiments with silage maize monoculture. Over a period of 26 years, the content of carbon in topsoil decreased by 22% in control unfertilized plots compared to 25% and 26% in treatments fertilized annually with mineral nitrogen. With annual wheat straw application (together with mineral N), the content of CSOM decreased by 8%. Contrary to that, the annual application of farmyard manure resulted in a CSOM increase of 16%. The ratio of carbon produced by maize related to total topsoil CSOM content ranged between 8.1–11.8%. In plots with mineral N fertilization, this ratio was always higher than in the unfertilized control plots. With the weaker soil extraction agent (CaCl2), the ratio of carbon produced by maize was determined to be 17.9–20.7%. With stronger extraction agent (pyrophosphate) it was only 10.2–14.6%. This shows that maize produced mostly unstable carbon compounds. Mineral N application resulted in stronger mineralization of original and stable organic matter compared to the unfertilized control. However, the increase of maize-produced carbon content in fertilized plots did not compensate for the decrease of “old” organic matter. As a result, a tendency to decrease total CSOM content in plots with mineral N applied was observed.
Therapeutic Application of Betalains: A Review
Authors: Madadi Elaheh , Mazloum-Ravasan Sahand , Yu Jae Sik , Ha Ji Won , Hamishehkar Hamed , Kim Ki Hyun
Published: September 2020

Anthocyanins, betalains, riboflavin, carotenoids, chlorophylls and caramel are the basic natural food colorants used in modern food manufacture. Betalains, which are composed of red–violet betacyanin and yellow betaxanthins, are water-soluble pigments that color flowers and fruits. Betalains are pigments primarily produced by plants of the order Caryophyllales. Because of their anti-inflammatory, cognitive impairment, anticancer and anti-hepatitis properties, betalains are useful as pharmaceutical agents and dietary supplements. Betalains also exhibit antimicrobial and antimalarial effects, and as an example, betalain-rich Amaranthus spinosus displays prominent antimalarial activity. Studies also confirmed the antidiabetic effect of betalains, which reduced glycemia by 40% without causing weight loss or liver impairment. These findings show that betalain colorants may be a promising alternative to the synthetic dyes currently used as food additives.
Comparative Analysis of Volatile Compounds of Gamma-Irradiated Mutants of Rose (Rosa hybrida)
Authors: Ryu Jaihyunk , Lyu Jae Il , Kim Dong-Gun , Kim Jung-Min , Jo Yeong Deuk , Kang Si-Yong , Kim Jin-Baek , Ahn Joon-Woo , Kim Sang Hoon
Published: September 2020

Roses are one of the most important floricultural crops, and their essential oils have long been used for cosmetics and aromatherapy. We investigated the volatile compound compositions of 12 flower-color mutant variants and their original cultivars. Twelve rose mutant genotypes were developed by treatment with 70 Gy of 60Co gamma irradiation of six commercial rose cultivars. Essential oils from the flowers of the 18 genotypes were analyzed by gas chromatography–mass spectrometry. Seventy-seven volatile compounds were detected, which were categorized into six classes: Aliphatic hydrocarbons, aliphatic alcohols, aliphatic ester, aromatic compounds, terpene alcohols, and others. Aliphatic (hydrocarbons, alcohols, and esters) compounds were abundant categories in all rose flowers. The CR-S2 mutant had the highest terpene alcohols and oil content. Three (CR-S1, CR-S3, and CR-S4) mutant genotypes showed higher ester contents than their original cultivar. Nonacosane, 2-methylhexacosane, and 2-methyltricosane were major volatile compounds among all genotypes. Hierarchical cluster analysis (HCA) of the rose genotypes gave four groups according to grouping among the 77 volatile compounds. In addition, the principal component analysis (PCA) model was successfully applied to distinguish most attractive rose lines. These findings will be useful for the selection of rose genotypes with improved volatile compounds.
Genetic Diversity and Population Structure of Maize Inbred Lines with Varying Levels of Resistance to Striga Hermonthica Using Agronomic Trait-Based and SNP Markers
Authors: Stanley Adekemi , Menkir Abebe , Paterne Agre , Ifie Beatrice , Tongoona Pangirayi , Unachukwu Nnanna , Meseka Silvestro , Mengesha Wende , Gedil Melaku
Published: September 2020

Striga hermonthica is a serious biotic stress limiting maize production in sub-Saharan Africa. The limited information on the patterns of genetic diversity among maize inbred lines derived from source germplasm with mixed genetic backgrounds limits the development of inbred lines, hybrids, and synthetics with durable resistance to S. hermonthica. This study was conducted to assess the level of genetic diversity in a panel of 150 diverse maize inbred lines using agronomic and molecular data and also to infer the population structure among the inbred lines. Ten Striga-resistance-related traits were used for the phenotypic characterization, and 16,735 high-quality single-nucleotide polymorphisms (SNPs), identified by genotyping-by-sequencing (GBS), were used for molecular diversity. The phenotypic and molecular hierarchical cluster analyses grouped the inbred lines into five clusters, respectively. However, the grouping patterns between the phenotypic and molecular hierarchical cluster analyses were inconsistent due to non-overlapping information between the phenotypic and molecular data. The correlation between the phenotypic and molecular diversity matrices was very low (0.001), which is in agreement with the inconsistencies observed between the clusters formed by the phenotypic and molecular diversity analyses. The joint phenotypic and genotypic diversity matrices grouped the inbred lines into three groups based on their reaction patterns to S. hermonthica, and this was able to exploit a broad estimate of the actual diversity among the inbred lines. The joint analysis shows an invaluable insight for measuring genetic diversity in the evaluated materials. The result indicates that wide genetic variability exists among the inbred lines and that the joint diversity analysis can be utilized to reliably assign the inbred lines into heterotic groups and also to enhance the level of resistance to Striga in new maize varieties.
Research Progress and Development Demand of Nanocellulose Reinforced Polymer Composites
Authors: Shen Renjie , Xue Shiwen , Xu Yanru , Liu Qi , Feng Zhang , Ren Hao , Zhai Huamin , Kong Fangong
Published: September 2020

Nanocellulose is a type of nanomaterial with high strength, high specific surface area and high surface energy. Additionally, it is nontoxic, harmless, biocompatible and environmentally friendly and can be extracted from biomass resources. The surface groups of cellulose show high surface energy and binding activity on the nanoscale and can be modified by using various methods. Because nanocellulose has a high elastic modulus, rigidity and a low thermal expansion coefficient, it is an excellent material for polymer reinforcement. This paper summarizes the reinforcement mechanisms of nanocellulose polymer composites with a focus on the role of theoretical models in elucidating these mechanisms. Furthermore, the influence of various factors on the properties of nanocellulose reinforced polymer composites are discussed in combination with analyses and comparisons of specific research results in related fields. Finally, research focus and development directions for the design of high-performance nanocellulose reinforced polymer composites are proposed.
Design of Electrochemically Effective Double-Layered Cation Exchange Membranes for Saline Water Electrolysis
Authors: Park In Kee , Lee Dong-Hoon , Lee Chang Hyun
Published: September 2020

Saline water electrolysis (SWE) is an electrochemical process to simultaneously produce hydrogen (H2), chlorine (Cl2), and sodium hydroxide (NaOH) with high purity levels (e.g., 99.999%) by applying electric power to saline water. The state-of-the art SWE membrane, Flemion®, has excellent chemical resistance to harsh SWE conditions, but still needs to lower its energy consumption by reducing its ohmic resistance to Na+ ion transport. Meanwhile, most of cation exchange membranes (CEMs) have been suffering from chemical degradation under the alkaline conditions, owing to their single layer matrices composed of sulfonic acid moieties, though they show fast Na+ ion transport behavior. Here double-layered SWE membranes were prepared on the basis of design strategies composed of the incorporation of a chemically stable carboxylic acid layer (C layer) via UV irradiation onto one surface of perfluorinated Nafion®212 membrane chosen as one of commercially available CEMs, and the thickness control of the C layer. The resulting membranes showed excellent SWE performances and improved electrochemical service life, when compared with those of Nafion®212 and Flemion®, respectively.
Thermal Kinetics of a Lignin-Based Flame Retardant
Authors: Liang Xiaoxuan , Hu Qixiang , Wang Xu , Li Liang , Dong Yuguo , Sun Chang , Hu Chengjuan , Gu Xiaoli
Published: September 2020

In order to improve the thermal property of epoxy resin (EP), a lignin-based flame retardant was prepared. Focusing on the lignin-based flame retardant, this paper investigates its pyrolysis behavior and kinetics via a thermogravimetric analyzer coupled with Fourier transform infrared spectrometry (TG–FTIR). Based on the FTIR result, which showed a peak at 1222 cm−1, it was assigned a syringyl structure. Its absorption peak intensity was enhanced and this meant that the phenolization of the lignin was successful. Thermogravimetry/derivative thermogravimetry (TG/DTG) results showed that the carbon residues of F-lignin and F-lignin@APP were reduced to 33.5% and 37.5%, respectively. In addition, the maximum decomposition rate of F-lignin@APP20/EP is 11.8%/min, which is 8%/min and 4.7%/min lower than for EP and Al-lignin, respectively. The char residue of F-lignin@APP20/EP is 32.5%, which is much higher than for EP. Lower decomposition rate and higher char residue indicate the improvement of thermal stability of EP by F-lignin@APP. Moreover, the kinetics of Al-lignin20/EP and F-lignin@APP20/EP were conducted by two kinetic methods: Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS). It was concluded that the pyrolysis process of Al-lignin 20/EP and F-lignin@APP 20/EP could be divided into three stages, while the value and growth rate of the activation energy of F-lignin@APP 20/EP were much higher than that of Al-lignin 20/EP in stage III.
Mixing of Bi-Dispersed Milli-Beads in a Rotary Drum. Mechanical Segregation Analyzed by Lab-Scale Experiments and DEM Simulation
Authors: Mesnier Aline , Peczalski Roman , Mollon Guilhem , Vessot-Crastes Séverine
Published: September 2020

Mechanical flow and segregation phenomena within a bed composed of milli-metric size spherical beads rotated in a horizontal drum were investigated. The beads population was bi-dispersed, with two kinds of binary (half by half) compositions: a bi-size bed with two different sizes and a bi-density bed with two different densities. The distributions of the beads were observed optically on the front side of the bed by means of a lab-scale drum prototype. Different numbers and lengths of peripheral straight baffles were tested as well as different drum filling ratios. The photographical data were processed to obtain the front layer mechanical segregation index. This experimental index was compared to the simulated one, obtained by means of commercial discrete element software EDEM. The simulations were corroborated by the experiments provided that the friction coefficients of the discrete elements method (DEM) model were correctly adjusted. The global segregation index was also calculated from simulation data for all considered cases and its values were lower and less sensitive to baffles’ configurations than those for the front layer.
Membrane System-Based Improved Neural Networks for Time-Series Anomaly Detection
Authors: Guo Wenxiang , Liu Xiyu , Xiang Laisheng
Published: September 2020

Anomaly detection in time series has attracted much attention recently and is quite a challenging task. In this paper, a novel deep-learning approach (AL-CNN) that classifies the time series as normal or abnormal with less domain knowledge is proposed. The proposed algorithm combines Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) to effectively model the spatial and temporal information contained in time-series data, the techniques of Squeeze-and-Excitation are applied to implement the feature recalibration. However, the difficulty of selecting multiple parameters and the long training time of a single model make AL-CNN less effective. To alleviate these challenges, a hybrid dynamic membrane system (HM-AL-CNN) is designed which is a new distributed and parallel computing model. We have performed a detailed evaluation of this proposed approach on three well-known benchmarks including the Yahoo S5 datasets. Experiments show that the proposed method possessed a robust and superior performance than the state-of-the-art methods and improved the average on three used indicators significantly.
State of Science Assessment of Remote Sensing of Great Lakes Coastal Wetlands: Responding to an Operational Requirement
Authors: White Lori , Ryerson Robert A. , Pasher Jon , Duffe Jason
Published: September 2020

The purpose of this research was to develop a state of science synthesis of remote sensing technologies that could be used to track changes in Great Lakes coastal vegetation for the Great Lakes-St. Lawrence River Adaptive Management (GLAM) Committee. The mapping requirements included a minimum mapping unit (MMU) of either 2 × 2 m or 4 × 4 m, a digital elevation model (DEM) accuracy in x and y of 2 m, a “z” value or vertical accuracy of 1–5 cm, and an accuracy of 90% for the classes of interest. To determine the appropriate remote sensing sensors, we conducted an extensive literature review. The required high degree of accuracy resulted in the elimination of many of the remote sensing sensors used in other wetland mapping applications including synthetic aperture radar (SAR) and optical imagery with a resolution >1 m. Our research showed that remote sensing sensors that could at least partially detect the different types of wetland vegetation in this study were the following types: (1) advanced airborne “coastal” Airborne Light Detection and Ranging (LiDAR) with either a multispectral or a hyperspectral sensor, (2) colour-infrared aerial photography (airplane) with (optimum) 8 cm resolution, (3) colour-infrared unmanned aerial vehicle (UAV) photography with vertical accuracy determination rated at 10 cm, (4) colour-infrared UAV photography with high vertical accuracy determination rated at 3–5 cm, (5) airborne hyperspectral imagery, and (6) very high-resolution optical satellite data with better than 1 m resolution.
Comparison of Filters for Archaeology-Specific Ground Extraction from Airborne LiDAR Point Clouds
Authors: Štular Benjamin , Lozić Edisa
Published: September 2020

Identifying bare-earth or ground returns within point cloud data is a crucially important process for archaeologists who use airborne LiDAR data, yet there has thus far been very little comparative assessment of the available archaeology-specific methods and their usefulness for archaeological applications. This article aims to provide an archaeology-specific comparison of filters for ground extraction from airborne LiDAR point clouds. The qualitative and quantitative comparison of the data from four archaeological sites from Austria, Slovenia, and Spain should also be relevant to other disciplines that use visualized airborne LiDAR data. We have compared nine filters implemented in free or low-cost off-the-shelf software, six of which are evaluated in this way for the first time. The results of the qualitative and quantitative comparison are not directly analogous, and no filter is outstanding compared to the others. However, the results are directly transferable to real-world problem-solving: Which filter works best for a given combination of data density, landscape type, and type of archaeological features? In general, progressive TIN (software: lasground_new) and a hybrid (software: Global Mapper) commercial filter are consistently among the best, followed by an open source slope-based one (software: Whitebox GAT). The ability of the free multiscale curvature classification filter (software: MCC-LIDAR) to remove vegetation is also commendable. Notably, our findings show that filters based on an older generation of algorithms consistently outperform newer filtering techniques. This is a reminder of the indirect path from publishing an algorithm to filter implementation in software.
Assessment of the Capability of Sentinel-2 Imagery for Iron-Bearing Minerals Mapping: A Case Study in the Cuprite Area, Nevada
Authors: Ge Wenyan , Cheng Qiuming , Jing Linhai , Wang Fei , Zhao Molei , Ding Haifeng
Published: September 2020

With several bands covering iron-bearing mineral spectral features, Sentinel-2 has advantages for iron mapping. However, due to the inconsistent spatial resolution, the sensitivity of Sentinel-2 data to detect iron-bearing minerals may be decreased by excluding the 60 m bands and neglecting the 20 m vegetation red-edge bands. Hence, the capability of Sentinel-2 for iron-bearing minerals mapping were assessed by applying a multivariate (MV) method to pansharpen Sentinel-2 data. Firstly, the Sentinel-2 bands with spatial resolution 20 m and 60 m (except band 10) were pansharpened to 10 m. Then, extraction of iron-bearing minerals from the MV-fused image was explored in the Cuprite area, Nevada, USA. With the complete set of 12 bands with a fine spatial resolution, three band ratios (6/1, 6/8A and (6 + 7)/8A) of the fused image were proposed for the extraction of hematite + goethite, hematite + jarosite and the mixture of iron-bearing minerals, respectively. Additionally, band ratios of Sentinel-2 data for iron-bearing minerals in previous studies were modified with substitution of narrow near infrared band 8A for band 8. Results demonstrated that the capability for detection of iron-bearing minerals using Sentinel-2 data was improved by consideration of two extra bands and the unified fine spatial resolution.
Explanation of InSAR Phase Disturbances by Seasonal Characteristics of Soil and Vegetation
Authors: Westerhoff Rogier , Steyn-Ross Moira
Published: September 2020

Seasonal phase disturbances in satellite Interferometric Synthetic Aperture Radar (InSAR) measurements have been reported in other studies to suggest sub-centimetre land surface terrain motion. These have been interpreted in various ways because they correlate with multiple other (sub-)seasonal signatures of, e.g., clay swelling/shrinkage and groundwater level. Recent microwave radar studies mention the occurrence of phase disturbances in different soil types and soil moisture. This study further explored this topic by modeling phase disturbances caused by both soil and vegetation surface characteristics and aimed to interpret what their possible effects on InSAR-interpreted terrain motion is. Our models, based on fundamental microwave reflection and transmission theory, found phase disturbances caused by seasonal variation of soil and vegetation that have the same magnitude as interpreted seasonal land movement in earlier InSAR studies. We showed that small, temporal differences in soil moisture and vegetation can lead to relatively large phase disturbances in InSAR measurements. These disturbances are a result of waves having to comply with boundary conditions at the interface between media with different dielectric properties. The findings of this study explain the seasonal variations found in other InSAR studies and will therefore bring new insights and alternative explanations to help improve interpretation of InSAR-derived seasonal terrain motion.
Monitoring of Chestnut Trees Using Machine Learning Techniques Applied to UAV-Based Multispectral Data
Authors: Pádua Luís , Marques Pedro , Martins Luís , Sousa António , Peres Emanuel , Sousa Joaquim J.
Published: September 2020

Phytosanitary conditions can hamper the normal development of trees and significantly impact their yield. The phytosanitary condition of chestnut stands is usually evaluated by sampling trees followed by a statistical extrapolation process, making it a challenging task, as it is labor-intensive and requires skill. In this study, a novel methodology that enables multi-temporal analysis of chestnut stands using multispectral imagery acquired from unmanned aerial vehicles is presented. Data were collected in different flight campaigns along with field surveys to identify the phytosanitary issues affecting each tree. A random forest classifier was trained with sections of each tree crown using vegetation indices and spectral bands. These were first categorized into two classes: (i) absence or (ii) presence of phytosanitary issues. Subsequently, the class with phytosanitary issues was used to identify and classify either biotic or abiotic factors. The comparison between the classification results, obtained by the presented methodology, with ground-truth data, allowed us to conclude that phytosanitary problems were detected with an accuracy rate between 86% and 91%. As for determining the specific phytosanitary issue, rates between 80% and 85% were achieved. Higher accuracy rates were attained in the last flight campaigns, the stage when symptoms are more prevalent. The proposed methodology proved to be effective in automatically detecting and classifying phytosanitary issues in chestnut trees throughout the growing season. Moreover, it is also able to identify decline or expansion situations. It may be of help as part of decision support systems that further improve on the efficient and sustainable management practices of chestnut stands.
Evaluation of Different Radiative Transfer Models for Microwave Backscatter Estimation of Wheat Fields
Authors: Weiß Thomas , Ramsauer Thomas , Löw Alexander , Marzahn Philip
Published: September 2020

This study aimed to analyze existing microwave surface (Oh, Dubois, Water Cloud Model “WCM”, Integral Equation Model “IEM”) and canopy (Water Cloud Model “WCM”, Single Scattering Radiative Transfer “SSRT”) Radiative Transfer (RT) models and assess advantages and disadvantages of different model combinations in terms of VV polarized radar backscatter simulation of wheat fields. The models are driven with field measurements acquired in 2017 at a test site near Munich, Germany. As vegetation descriptor for the canopy models Leaf Area Index (LAI) was used. The effect of empirical model parameters is evaluated in two different ways: (a) empirical model parameters are set as static throughout the whole time series of one growing season and (b) empirical model parameters describing the backscatter attenuation by the canopy are treated as non-static in time. The model results are compared to a dense Sentinel-1 C-band time series with observations every 1.5 days. The utilized Sentinel-1 time series comprises images acquired with different satellite acquisition geometries (different incidence and azimuth angles), which allows us to evaluate the model performance for different acquisition geometries. Results show that total LAI as vegetation descriptor in combination with static empirical parameters fit Sentinel-1 radar backscatter of wheat fields only sufficient within the first half of the vegetation period. With the saturation of LAI and/or canopy height of the wheat fields, the observed increase in Sentinel-1 radar backscatter cannot be modeled. Probable cause are effects of changes within the grains (both structure and water content per leaf area) and their influence on the backscatter. However, model results with LAI and non-static empirical parameters fit the Sentinel-1 data well for the entire vegetation period. Limitations regarding different satellite acquisition geometries become apparent for the second half of the vegetation period. The observed overall increase in backscatter can be modeled, but a trend mismatch between modeled and observed backscatter values of adjacent time points with different acquisition geometries is observed.
Development and Application of HECORA Cloud Retrieval Algorithm Based On the O2-O2 477 nm Absorption Band
Authors: Wang Shuntian , Liu Cheng , Zhang Wenqiang , Hao Nan , Gimeno García Sebastián , Xing Chengzhi , Zhang Chengxin , Su Wenjing , Liu Jianguo
Published: September 2020

In this paper, we present the Hefei EMI Cloud Retrieval Algorithm (HECORA), which uses information from the O2-O2 absorption band around 477 nm to retrieve effective cloud fraction and effective cloud pressure from satellite observations. The retrieved cloud information intends to improve the atmospheric trace gas products based on the Environment Monitoring Instrument (EMI) spectrometer. The HECORA method builds on OMCLDO2 and presents some evolutions. The Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model has been used to produce the Top of the Atmosphere (TOA) reflectance Look-up Tables (LUT) as a function of the cloud fraction and cloud pressure. Applying the Differential Optical Absorption Spectroscopy (DOAS) technique to the synthetic reflectance LUT, the reflectance spectra can be associated with O2-O2 geometrical vertical column densities (VCDgeo) and continuum reflectance. This is the core of the retrieval method, since there is a one-to-one relationship between O2-O2 VCDgeo and continuum reflectance, on the one hand, and effective cloud fraction and effective cloud pressure, on the other hand, for a given illumination and observing geometry and given surface height and surface albedo. We first used the VLIDORT synthetic spectra to verify the HECORA algorithm and obtained good results in both the Lambertian cloud model and the scattering cloud model. Secondly, HECORA is applied to OMI and TROPOMI and compared with OMCLDO2, FRESCO+, and OCRA/ROCINN cloud products. Later, the cloud pressure results from TROPOMI observations obtained using HECORA and FRESCO+ are compared with the CALIOP Cloud Layer product. HECORA is closer to the CALIOP results under low cloud conditions, while FRESCO+ is closer to high clouds due to the higher sensitivity of the O2 A-band to cloud vertical information. Finally, HECORA is applied to the TROPOMI NO2 retrieval. Validation of the tropospheric NO2 VCD with ground-based MAX-DOAS measurements shows that choosing HECORA cloud products to correct for photon path variations on the TROPOMI tropospheric NO2 VCD retrievals has better performance than using FRESCO+ under low cloud conditions. In conclusion, this paper shows that the HECORA cloud products are in good agreement with the well-established cloud products and that they are suitable for correcting the effect of cloud in trace gas retrievals. Therefore, HECORA has the potential to be applied to EMI.
Performance Characterization of the Smartphone Video Guidance Sensor as Vision-Based Positioning System
Authors: Hariri Nasir , Gutierrez Hector , Rakoczy John , Howard Richard , Bertaska Ivan
Published: September 2020

The Smartphone Video Guidance Sensor (SVGS) is a vision-based sensor that computes the six-state position and orientation vector of a target relative to a coordinate system attached to a smartphone. This paper presents accuracy-characterization measurements of the Smartphone Video Guidance Sensor (SVGS) to assess its performance as a position and attitude estimator, evaluating its accuracy in linear and angular motion for different velocities and various types of targets based on the mean and standard deviation errors between SVGS estimates and known motion profiles, in both linear and angular motions. The study also examines the effects of target velocity and sampling rate on the overall performance of SVGS and provides an overall assessment of SVGS’ performance as a position/attitude estimator. While the error metrics are dependent on range and camera resolution, the results of this paper can be scaled to other operational conditions by scaling the blob size in pixels (the light markers identified in the images) relative to the total resolution (number of pixels) of the image. The error statistics of SVGS enable its incorporation (by synthesis of a Kalman estimator) in advanced motion-control systems for navigation and guidance.
Ethnopharmacology, Therapeutic Properties and Nutritional Potentials of Carpobrotus edulis: A Comprehensive Review
Authors: Akinyede Kolajo Adedamola , Ekpo Okobi Eko , Oguntibeju Oluwafemi Omoniyi
Published: September 2020

Carpobrotus edulis, formerly known as Mesembryanthemum edule L, belongs to the Aizoaceae family of plants. It is a facultative halophytic invasive medicinal and edible succulent plant that is native to South Africa and is distributed worldwide. Hitherto, this plant appears to be mainly known for its ornamental use in decorations, soil stabilization, and erosion control, and not for its many potential medicinal and nutritional benefits, thus suggesting its underutilization. This review presents cogent and comprehensive information on the distribution, ethnomedicinal use, phytochemistry, pharmacology, toxicology, and nutritional value of Carpobrotus edulis and provides the rationale for further pharmacognostic research that will validate its many folkloric medicinal and nutraceutical claims, and promote its standardization into a commercially available product. The reported traditional use of this plant for the treatment of sinusitis, diarrhoea, tuberculosis, infantile eczema, fungal and bacterial infections, oral and vaginal thrush, high blood pressure, diabetes, wound infections, spider and tick bites, sore throat as well as mouth infections are well documented. Its therapeutic activities such as anti-proliferative, antioxidant, antifungal, antibacterial, antidiabetic, anti-inflammatory, cytotoxicity, and nutritional value have also been reported to be attributable to the array of phytoconstituents present in the plant. These have promoted renewed research interests into this valuable medicinal plant with a view to repositioning and expanding its uses from the current predominantly ornamental and environmental management role to include phytotherapeutical applications through scientific validation studies that will improve its value for the drug discovery process as well as its contribution to food security.
A Cross-Scale Analysis of the Correlation between Daytime Air Temperature and Heterogeneous Urban Spaces
Authors: Du Sihong , Li Yanxia , Wang Chao , Tian Zhichao , Lu Yongdong , Zhu Sijie , Shi Xing
Published: September 2020

The problem of the urban thermal environment is becoming increasingly noticeable in the process of modern urban development. The temperature patterns in central business districts can be more complicated due to the heterogeneous urban spaces and diverse building forms, which need more cross-scale research. This study investigated the correlation between air temperature and urban morphology in a heterogeneous urban district in northeastern China. The thermal environment of the studied district in the summertime was simulated by ENVI-met. A total of 12 morphological indicators were selected to describe the geometric features of the studied district. Curve estimation was employed to quantify the correlation between air temperature and morphological indicators. The results indicate different effects of the morphological indicators of the air temperature on different scales. On a mesoscale, the compactness (Com), building footprint ratio (BFR), enclosure degree (ED) and total height to total floor area ratio (HA) had a significant correlation with the air temperature. On a microscale, only the BFR and ED had relatively steady correlations with the air temperature. The correlation between air temperature and morphological indicators could be influenced by the heterogeneity of the urban morphology, including the diversity of the heights and footprints of buildings and the irregularity of building horizontal arrangement.
A Simple Home-Based Lifestyle Intervention Program to Improve Cardiac Autonomic Regulation in Patients with Increased Cardiometabolic Risk
Authors: Lucini Daniela , Malacarne Mara , Gatzemeier Wolfgang , Pagani Massimo
Published: September 2020

Lifestyle modification programs (LMP) represent a new approach to cardiometabolic/oncologic risk reduction. Successful LMP in clinical practice must be feasible, cost effective, efficacious and consider home-based exercise. Likewise, multiple mechanisms implied in cardiometabolic risk reduction such as cardiac autonomic regulation (CAR) should be easily evidenced, in spite of the computational complexity involved. This goal could be facilitated by employing novel, friendlier, simpler techniques, such as the Autonomic Nervous System Index (ANSI), which can be treated as a proxy of CAR. In this observational study, we introduce a simple LMP (based on cognitive behavioral strategies and patient-tailored prescription of nutrition and home-based exercise, managed by a single physician) into the currently existing clinical practice of secondary cardiometabolic prevention. In 26 subjects, we assessed CAR (autoregressive spectral analysis of cardiovascular variabilities), body mass composition (bioelectrical impedance analysis) and stress perception (questionnaires). After LMP, ANSI and lipid profile were improved; % of fat mass, waist circumference and stress perception were reduced. We conclude that this preliminary, proof of concept study provides significant evidence in favor of the hypothesis that it is possible to introduce a convenient, cost effective LMP into the currently existing clinical practice of secondary cardiometabolic prevention. Findings suggest a successful comprehensive behavioral change, possibly facilitated by the simplified approach employed in this study, capable of improving cardiac autonomic regulation in addition to body mass composition and stress perception.