bluuebunny/crossref_metadata_2025 huggingface dataset:
Antimicrobial and Toxicity Evaluation of Imidazolium-Based Dicationic Ionic Liquids with Dicarboxylate Anions
Authors: Kuhn Bruna L. , Kaminski Taís F. A. , Carvalho Ânderson R. , Fuentefria Alexandre M. , Johann Bianca M. B. C. , da Silva Edilma E. , Silveira Gustavo P. , da Silveira Tássia L. , Soares Félix A. A. , Zanatta Nilo , Frizzo Clarissa P.
Published: April 2021

Imidazolium-based dicationic ILs (DILs) presenting antimicrobial activity and relatively low toxicity are highly desirable and are envisioned for use in live tissue to prevent bacterial or fungal infections. In this context, we present here DILs with dicarboxylate anions [Cn(MIM)2[Cn(MIM)2][CO2-(CH2)mCO2], in which n = 4, 6, 8, and 10, and m = 0, 1, 2, 3, 4, and 5. The results showed that DILs with an alkyl chain spacer of ten carbons were active against yeasts and the bacterial strains tested. However, most of the DILs were cytotoxic and toxic at 1 mM. By contrast, DILs with alkyl chains possessing less than ten carbons were active against some specific Candidas and bacteria (mainly S. aureus), and they showed moderate cytotoxicity. The best activity against Gram-positive bacteria was observed for [C4(MIM)2][Pim] toward MRSA. For the DILs described herein, their level of toxicity against C. elegans was lower than that of most of the mono- and dicationic IL analogs with other anions. Our results showed that the presence of carboxylate anions reduces the toxicity of DILs compared to DILs containing halide anions, which is particularly significant to the means of designing biologically active compounds in antimicrobial formulations.
Synthesis and Evaluation of the Cytotoxic Activity of Water-Soluble Cationic Organometallic Complexes of the Type [Pt(η1-C2H4OMe)(L)(Phen)]+ (L = NH3, DMSO; Phen = 1,10-Phenanthroline)
Authors: De Castro Federica , Stefàno Erika , Migoni Danilo , Iaconisi Giorgia N. , Muscella Antonella , Marsigliante Santo , Benedetti Michele , Fanizzi Francesco P.
Published: April 2021

Starting from the [PtCl(η1-C2H4OMe)(phen)] (phen = 1,10-phenanthroline, 1) platinum(II) precursor, we synthesized and characterized by multinuclear NMR new [Pt(η1-C2H4OMe)(L)(phen)]+ (L = NH3, 2; DMSO, 3) complexes. These organometallic species, potentially able to interact with cell membrane organic cation transporters (OCT), violating some of the classical rules for antitumor activity of cisplatin analogues, were evaluated for their cytotoxicity. Interestingly, despite both complexes 2 and 3 resulting in greater cell uptake than cisplatin in selected tumor cell lines, only 3 showed comparable or higher antitumor activity. General low cytotoxicity of complex 2 in the tested cell lines (SH-SY5Y, SK-OV-3, Hep-G2, Caco-2, HeLa, MCF-7, MG-63, ZL-65) appeared to depend on its stability towards solvolysis in neutral water, as assessed by NMR monitoring. Differently, the [Pt(η1-C2H4OMe)(DMSO)(phen)]+ (3) complex was easily hydrolyzed in neutral water, resulting in a comparable or higher cytotoxicity in cancer cells with respect to cisplatin. Further, both IC50 values and the uptake profiles of the active complex appeared quite different in the used cell lines, suggesting the occurrence of diversified biological effects. Nevertheless, further studies on the metabolism of complex 3 should be performed before planning its possible use in tissue- and tumor-specific drug design.
Dynamics & Spectroscopy with Neutrons—Recent Developments & Emerging Opportunities
Authors: Drużbicki Kacper , Gaboardi Mattia , Fernandez-Alonso Felix
Published: April 2021

This work provides an up-to-date overview of recent developments in neutron spectroscopic techniques and associated computational tools to interrogate the structural properties and dynamical behavior of complex and disordered materials, with a focus on those of a soft and polymeric nature. These have and continue to pave the way for new scientific opportunities simply thought unthinkable not so long ago, and have particularly benefited from advances in high-resolution, broadband techniques spanning energy transfers from the meV to the eV. Topical areas include the identification and robust assignment of low-energy modes underpinning functionality in soft solids and supramolecular frameworks, or the quantification in the laboratory of hitherto unexplored nuclear quantum effects dictating thermodynamic properties. In addition to novel classes of materials, we also discuss recent discoveries around water and its phase diagram, which continue to surprise us. All throughout, emphasis is placed on linking these ongoing and exciting experimental and computational developments to specific scientific questions in the context of the discovery of new materials for sustainable technologies.
The Study of pH Effects on Phase Transition of Multi-Stimuli Responsive P(NiPAAm-co-AAc) Hydrogel Using 2D-COS
Authors: Park Yeonju , Kim Minkyoung , Chung Hae-jin , Woo Ah-hyun , Noda Isao , Jung Young-mee
Published: April 2021

The temperature and mechanism of phase transition of poly(N-isopropylacrylamide-co-acrylic acid) [P(NiPAAm-co-AAc)], which is one of the multi-stimuli responsive polymers, were investigated at various pHs using infrared (IR) spectroscopy, two-dimensional (2D) gradient mapping, and two-dimensional correlation spectroscopy (2D-COS). The determined phase transition temperature of P(NiPAAm-co-AAc) at pH 4, 3, and 2 based on 2D gradient mapping and principal component analysis (PCA) showed that it decreases with decreasing pH, because COOH group in AAc changes with variation of pH. The results of 2D-COS analysis indicated that the phase transition mechanism of P(NiPAAm-co-AAc) hydrogel at pH4 is different from that at pH2 due to the effect of COOH group of AAc.
Thin-Film Processing of Polypropylene and Polystyrene Sheets by a Continuous Wave CO2 Laser with the Cu Cooling Base
Authors: Kameyama Nobukazu , Yoshida Hiroki , Fukagawa Hitoshi , Yamada Kotaro , Fukuda Mitsutaka
Published: April 2021

Carbon dioxide (CO2) laser is widely used in commercial and industrial fields to process various materials including polymers, most of which have high absorptivity in infrared spectrum. Thin-film processing by the continuous wave (CW) laser is difficult since polymers are deformed and damaged by the residual heat. We developed the new method to make polypropylene (PP) and polystyrene (PS) sheets thin. The sheets are pressed to a Cu base by extracting air between the sheets and the base during laser processing. It realizes to cut the sheets to around 50 µm thick with less heat effects on the backside which are inevitable for thermal processing using the CW laser. It is considered that the boundary between the sheets and the base is in thermal equilibrium and the base prevents the sheets from deforming to support the backside. The method is applicable to practical use since it does not need any complex controls and is easy to install to an existing equipment with a minor change of the stage.
Solution Crystallization of Polycarbonate Surfaces for Hydrophobic State: Water Droplet Dynamics and Life Cycle Assessment towards Self-Cleaning Applications
Authors: Yilbas Bekir Sami , Abubakar Abba Abdulhamid , Al-Qahtani Hussain , Shuja Shahzada Zaman , Shaukat Mian Mobeen , Sahin Ahmet Z. , Al-Sharafi Abdullah , Bahatab Saeed
Published: April 2021

Polycarbonate sheets are optically transparent and have the potential to be used as one of the cover materials for PV applications. Solution treatment of polycarbonate surfaces enables to create surface texture topology giving rise to a hydrophobic state, which is favorable for self-cleaning applications. In the present study, hydrophobization of polycarbonate surface is investigated via crystallization of surface by a one-step process. The influence of texture topology, which is created via crystallization, on water droplet mobility and optical transmittance is examined. Findings revealed that solution treatment, using acetone, results in crystallized polycarbonate surfaces with a hydrophobic state. Depending on the treatment duration, the texture characteristics of crystallized surface change while influencing the water contact angle hysteresis. This in turn affects the droplet mobility over the inclined crystallized surface and alters the UV visible transmittance. Moreover, the droplet mobility improves and dust mitigation rates from the treated surface increase as the solution treatment duration are reduced to 2 min. Oil impregnated samples result in improved UV visible transmittance; however, droplet motion changes from rolling to sliding over the surface. A sliding water droplet enables the removal of the dust particles from the oil-impregnated sample surface.
Design and Evaluation of Hybrid Composite Plates for Ballistic Protection: Experimental and Numerical Investigations
Authors: Alkhatib Farah , Mahdi Elsadig , Dean Aamir
Published: April 2021

In this paper, hybrid composite plates for ballistic protection were investigated experimentally and numerically, with a target to reduce the weight of currently used body armor inserts and, at the same time, satisfy the requirements of the National Institute of Justice’s (NIJ) ballistic protection standards. The current study has three phases to improve the ballistic plate’s energy absorption capability. The first phase is devoted to studying the effect of the material types, including three different fibers: carbon fiber, date palm fiber, and Kevlar fiber. The second phase is dedicated to studying the effect of hybridization within layers. The two previous phases’ results were analyzed to optimize the material based on the hybrid composite ballistic plate’s maximum energy absorption capability. The commercial finite element software package LS-DYNA was employed for numerical modeling and simulation. The hybrid composite ballistic plate could absorb more impact energy than the non-hybrid Kevlar plate with the same area density from the numerical simulation results. This study provides lighter-weight ballistic inserts with a high protection level, making movement easier for the wearer. The numerical results were verified by comparing results of a plate made of 40 layers of Kevlar with an actual ballistic test. The results indicated that the simulation results were conservative compared to the ballistic test.
Influence of Gamma Irradiation on Electric Cables Models: Study of Additive Effects by Mid-Infrared Spectroscopy
Authors: Maléchaux Astrid , Colombani Juliette , Amat Sandrine , Marque Sylvain R. A. , Dupuy Nathalie
Published: April 2021

Cables, especially their insulation and jacket materials made of polymers, are vulnerable to ageing degradation during normal operation. However, they must remain functional for the entire life of a nuclear power plant, or even in the event of an accident for cables with a safety requirement. This study focuses on models of crosslinked polyethylene (XLPE)-based insulation of cables and deals with the structure modification and the behavior of XLPE for nuclear applications due to the effect of additives. Various additives are added to the polymer formulation to evaluate their impact on ageing. The samples are irradiated at room temperature by several gamma doses, up to 374 kGy, with two dose rates (40 Gy/h and 300 Gy/h) and compared with a non-irradiated sample used as reference. To understand the impact of gamma irradiation on the materials, the principal component analysis (PCA) method is applied on spectra recorded through attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy. The results highlight the effects of ageing depending on the dose rate and on the formulation of the materials, with the identification of different degradation products. A curve resolution study compares the effects of different additives on polymer oxidation and shows that the low dose rate leads to a higher degradation than the high dose rate.
Probing the Release of Bupropion and Naltrexone Hydrochloride Salts from Biopolymeric Matrices of Diverse Chemical Structures
Authors: Siamidi Angeliki , Dedeloudi Aikaterini , Vlachou Marilena
Published: April 2021

In the last decades, the notion of including excipients in the formulations, as inert substances aiding production processes, has changed and they are recently viewed as multifunctional discrete entities. It is now well documented that excipients serve several roles, spreading from the stabilization and modified release, to providing biocompatible properties and targeting moieties. The aim of this study was to develop matrix-based oral drug delivery systems of bupropion hydrochloride (BUP·HCl) and naltrexone hydrochloride (NTX·HCl), suitable for releasing these active substances in a modified manner, providing a stable level of drug release, which is simultaneously therapeutically effective and non-toxic, thus reducing side effects, after a single dose administration, throughout the gastrointestinal tract. The new formulations, employing hydroxypropylmethycellulose (HPMC K15M) (a cellulosic polymer, which, generally hydrates to form a gelatinous layer that is critical to prevent wetting and rapid drug release from the matrices), poly(methacylic acid-co-ethyl acrylate) 1:1 (Eudragit® L100-55: effective for site specific drug delivery in intestine), poly(ethylene oxide) (PEO) (7 × 106: a high molecular weight polymer, water-soluble, in micro-granular powder form), as the rate controlling polymers, were chosen to lead to a “soothing out” release pattern of these drugs, at 0 ≤ t ≤ 120 min. Moreover, the release of the two drugs from the ulvan-based tablets, was found to follow the desired profile, throughout the entire course of the dissolution experiments.
Rapid Prototyping of Pneumatic Directional Control Valves
Authors: Blasiak Slawomir , Laski Pawel Andrzej , Takosoglu Jakub Emanuel
Published: April 2021

The main objective of the study was to design a pneumatic directional control valve for controlling pneumatic drives and produce it using a rapid prototyping technique. As the basic design assumption was to achieve high performance through a high flow rate and a low pressure drop, it was necessary to determine two flow parameters: the sonic conductance and the critical pressure ratio. The flow rate of compressed air and the diameters of the pneumatic conduits and fittings are important as they affect the rate of travel of the pneumatic cylinder piston. The 3D solid model of the directional control valve, developed in a CAD program, was used to simulate and optimize the flow rate. The analysis was performed by means of ANSYS CFX, a computational flow dynamics program. The main elements of the valve, i.e., the spool and the body, were produced using the PolyJet Matrix technology. The prototype was tested experimentally to determine the nominal flow-rate, calculate the flow parameters in accordance with the ISO 6358-1989 standard and compare them with the CFD simulation data. The simulation results showed very good agreement with the measurement data. The CFD analysis of the 3D solid model enabled us to optimize the flow of compressed air through the valve. The rapid prototyping method was found to be suitable to produce a fully functional directional control valve, which was confirmed through measurements at a test stand. The attempt to combine rapid prototyping used to fabricate pneumatic directional control valves with CFD used to simulate their operation was successful. The study shows that it is possible to design and construct a fully functional directional control valve characterized by high efficiency, high performance and a small pressure loss in a very short time and at a very low cost, which makes rapid prototyping superior to conventional methods of prototype making.
Mechanical Properties, Wettability and Thermal Degradation of HDPE/Birch Fiber Composite
Authors: Koffi Agbelenko , Mijiyawa Fayçal , Koffi Demagna , Erchiqui Fouad , Toubal Lotfi
Published: April 2021

Wood–plastic composites have emerged and represent an alternative to conventional composites reinforced with synthetic carbon fiber or glass fiber–polymer. A wide variety of wood fibers are used in WPCs including birch fiber. Birch is a common hardwood tree that grows in cool areas such as the province of Quebec, Canada. The effect of the filler proportion on the mechanical properties, wettability, and thermal degradation of high-density polyethylene/birch fiber composite was studied. High-density polyethylene, birch fiber and maleic anhydride polyethylene as coupling agent were mixed and pressed to obtain test specimens. Tensile and flexural tests, scanning electron microscopy, dynamic mechanical analysis, differential scanning calorimetry, thermogravimetry analysis and surface energy measurement were carried out. The tensile elastic modulus increased by 210% as the fiber content reached 50% by weight while the flexural modulus increased by 236%. The water droplet contact angle always exceeded 90°, meaning that the material remained hydrophobic. The thermal decomposition mass loss increased proportional with the percentage of fiber, which degraded at a lower temperature than the HDPE did. Both the storage modulus and the loss modulus increased with the proportion of fiber. Based on differential scanning calorimetry, neither the fiber proportion nor the coupling agent proportion affected the material melting temperature.
Effect of Cellulose Nanofibrils on the Properties of Jatropha Oil-Based Waterborne Polyurethane Nanocomposite Film
Authors: Amri Mohamad Ridzuan , Guan Chuah Teong , Osman Al-Edrus Syeed Saifulazry , Md Yasin Faizah , Mohamad Siti Fatahiyah
Published: April 2021

The objective of this work was to study the influence of cellulose nanofibrils (CNF) on the physical, mechanical, and thermal properties of Jatropha oil-based waterborne polyurethane (WBPU) nanocomposite films. The polyol to produce polyurethane was synthesized from crude Jatropha oil through epoxidation and ring-opening method. The chain extender, 1,6-hexanediol, was used to improve film elasticity by 0.1, 0.25, and 0.5 wt.% of CNF loading was incorporated to enhance film performance. Mechanical performance was studied using a universal test machine as specified in ASTM D638-03 Type V and was achieved by 0.18 MPa at 0.5 wt.% of CNF. Thermal gravimetric analysis (TGA) was performed to measure the temperature of degradation and the chemical crosslinking and film morphology were studied using Fourier-transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM). The results showed that when the CNF was incorporated, it was found to enhance the nanocomposite film, in particular its mechanical and thermal properties supported by morphology. Nanocomposite film with 0.5 wt.% of CNF showed the highest improvement in terms of tensile strength, Young’s modulus, and thermal degradation. Although the contact angle decreases as the CNF content increases, the effect on the water absorption of the film was found to be relatively small (<3.5%). The difference between the neat WPBU and the highest CNF loading film was not more than 1%, even after 5 days of being immersed in water.
Formation of the Traditional Chinese State Ritual System of Sacrifice to Mountain and Water Spirits
Authors: Jia Jinhua
Published: April 2021

Sacrifice to mountain and water spirits was already a state ritual in the earliest dynasties of China, which later gradually formed a system of five sacred peaks, five strongholds, four seas, and four waterways, which was mainly constructed by the Confucian ritual culture. A number of modern scholars have studied the five sacred peaks from different perspectives, yielding fruitful results, but major issues are still being debated or need to be plumbed more broadly and deeply, and the whole sacrificial system has not yet drawn sufficient attention. Applying a combined approach of religious, historical, geographical, and political studies, I provide here, with new discoveries and conclusions, the first comprehensive study of the formational process of this sacrificial system and its embodied religious-political conceptions, showing how these geographical landmarks were gradually integrated with religious beliefs and ritual-political institutions to become symbols of territorial, sacred, and political legitimacy that helped to maintain the unification and government of the traditional Chinese imperium for two thousand years. A historical map of the locations of the sacrificial temples for the eighteen mountain and water spirits is appended.
Validating Safety in Human–Robot Collaboration: Standards and New Perspectives
Authors: Valori Marcello , Scibilia Adriano , Fassi Irene , Saenz José , Behrens Roland , Herbster Sebastian , Bidard Catherine , Lucet Eric , Magisson Alice , Schaake Leendert , Bessler Jule , Prange-Lasonder Gerdienke B. , Kühnrich Morten , Lassen Aske B. , Nielsen Kurt
Published: April 2021

Human–robot collaboration is currently one of the frontiers of industrial robot implementation. In parallel, the use of robots and robotic devices is increasing in several fields, substituting humans in “4D”—dull, dirty, dangerous, and delicate—tasks, and such a trend is boosted by the recent need for social distancing. New challenges in safety assessment and verification arise, due to both the closer and closer human–robot interaction, common for the different application domains, and the broadening of user audience, which is now very diverse. The present paper discusses a cross-domain approach towards the definition of step-by-step validation procedures for collaborative robotic applications. To outline the context, the standardization framework is analyzed, especially from the perspective of safety testing and assessment. Afterwards, some testing procedures based on safety skills, developed within the framework of the European project COVR, are discussed and exemplary presented.
GazeEMD: Detecting Visual Intention in Gaze-Based Human-Robot Interaction
Authors: Shi Lei , Copot Cosmin , Vanlanduit Steve
Published: April 2021

In gaze-based Human-Robot Interaction (HRI), it is important to determine human visual intention for interacting with robots. One typical HRI interaction scenario is that a human selects an object by gaze and a robotic manipulator will pick up the object. In this work, we propose an approach, GazeEMD, that can be used to detect whether a human is looking at an object for HRI application. We use Earth Mover’s Distance (EMD) to measure the similarity between the hypothetical gazes at objects and the actual gazes. Then, the similarity score is used to determine if the human visual intention is on the object. We compare our approach with a fixation-based method and HitScan with a run length in the scenario of selecting daily objects by gaze. Our experimental results indicate that the GazeEMD approach has higher accuracy and is more robust to noises than the other approaches. Hence, the users can lessen cognitive load by using our approach in the real-world HRI scenario.
Distance Transform-Based Spectral-Spatial Feature Vector for Hyperspectral Image Classification with Stacked Autoencoder
Authors: Madani Hadis , McIsaac Kenneth
Published: April 2021

Pixel-wise classification of hyperspectral images (HSIs) from remote sensing data is a common approach for extracting information about scenes. In recent years, approaches based on deep learning techniques have gained wide applicability. An HSI dataset can be viewed either as a collection of images, each one captured at a different wavelength, or as a collection of spectra, each one associated with a specific point (pixel). Enhanced classification accuracy is enabled if the spectral and spatial information are combined in the input vector. This allows simultaneous classification according to spectral type but also according to geometric relationships. In this study, we proposed a novel spatial feature vector which improves accuracies in pixel-wise classification. Our proposed feature vector is based on the distance transform of the pixels with respect to the dominant edges in the input HSI. In other words, we allow the location of pixels within geometric subdivisions of the dataset to modify the contribution of each pixel to the spatial feature vector. Moreover, we used the extended multi attribute profile (EMAP) features to add more geometric features to the proposed spatial feature vector. We have performed experiments with three hyperspectral datasets. In addition to the Salinas and University of Pavia datasets, which are commonly used in HSI research, we include samples from our Surrey BC dataset. Our proposed method results compares favorably to traditional algorithms as well as to some recently published deep learning-based algorithms.
The Use of Superspheroids as Surrogates for Modeling Electromagnetic Wave Scattering by Ice Crystals
Authors: Sun Lan-Hui , Bi Lei , Yi Bingqi
Published: April 2021

Electromagnetic wave scattering by ice particles is commonly modeled by defining representative habits, including droxtals, columns, plates, and aggregates, although actual particles in the atmosphere can be even much more complex. In this study, we examined a superspheroidal approximation method for modeling electromagnetic wave scattering by ice crystals. Superspheroid can be associated with a shape index (SI) defined by the particle volume and average projected area. Corresponding to realistic ice crystals, suitable superspheroid models with the same SI (that means, identical volume and average projected area) and aspect ratio can be identified as surrogates for optical property calculations. We systematically compared the optical properties of ice crystals and superspheroids at 33 microwave bands in the range of 3–640 GHz and at three representative visible or infrared wavelengths (0.66, 2.13, and 11 μm). It was found that the single-scattering properties of compact ice crystal habits and their superspheroidal model particles were quite close. For an aggregate with sparse distribution of elements, a superspheroid model produces relatively large errors because the aspect ratio may not be sufficient to describe a particle shape. However, the optical similarity of a superspheroid and an aggregate is still encouraging.
Drone-Based Community Assessment, Planning, and Disaster Risk Management for Sustainable Development
Authors: Whitehurst Daniel , Friedman Brianna , Kochersberger Kevin , Sridhar Venkat , Weeks James
Published: April 2021

Accessible, low-cost technologies and tools are needed in the developing world to support community planning, disaster risk assessment, and land tenure. Enterprise-scale geographic information system (GIS) software and high-resolution aerial or satellite imagery are tools which are typically not available to or affordable for resource-limited communities. In this paper, we present a concept of aerial data collection, 3D cadastre modeling, and disaster risk assessment using low-cost drones and adapted open-source software. Computer vision/machine learning methods are used to create a classified 3D cadastre that contextualizes and quantifies potential natural disaster risk to existing or planned infrastructure. Building type and integrity are determined from aerial imagery. Potential flood damage risk to a building is evaluated as a function of three mechanisms: undermining (erosion) of the foundation, hydraulic pressure damage, and building collapse due to water load. Use of Soil and Water Assessment Tool (SWAT) provides water runoff estimates that are improved using classified land features (urban ecology, erosion marks) to improve flow direction estimates. A convolutional neural network (CNN) is trained to find these flood-induced erosion marks from high-resolution drone imagery. A flood damage potential metric scaled by property value estimates results in individual and community property risk assessments.
Semi-Supervised Segmentation for Coastal Monitoring Seagrass Using RPA Imagery
Authors: Hobley Brandon , Arosio Riccardo , French Geoffrey , Bremner Julie , Dolphin Tony , Mackiewicz Michal
Published: April 2021

Intertidal seagrass plays a vital role in estimating the overall health and dynamics of coastal environments due to its interaction with tidal changes. However, most seagrass habitats around the globe have been in steady decline due to human impacts, disturbing the already delicate balance in the environmental conditions that sustain seagrass. Miniaturization of multi-spectral sensors has facilitated very high resolution mapping of seagrass meadows, which significantly improves the potential for ecologists to monitor changes. In this study, two analytical approaches used for classifying intertidal seagrass habitats are compared—Object-based Image Analysis (OBIA) and Fully Convolutional Neural Networks (FCNNs). Both methods produce pixel-wise classifications in order to create segmented maps. FCNNs are an emerging set of algorithms within Deep Learning. Conversely, OBIA has been a prominent solution within this field, with many studies leveraging in-situ data and multiresolution segmentation to create habitat maps. This work demonstrates the utility of FCNNs in a semi-supervised setting to map seagrass and other coastal features from an optical drone survey conducted at Budle Bay, Northumberland, England. Semi-supervision is also an emerging field within Deep Learning that has practical benefits of achieving state of the art results using only subsets of labelled data. This is especially beneficial for remote sensing applications where in-situ data is an expensive commodity. For our results, we show that FCNNs have comparable performance with the standard OBIA method used by ecologists.
Land Cover-Specific Local Incidence Angle Correction: A Method for Time-Series Analysis of Forest Ecosystems
Authors: Paluba Daniel , Laštovička Josef , Mouratidis Antonios , Štych Přemysl
Published: April 2021

This study deals with a local incidence angle correction method, i.e., the land cover-specific local incidence angle correction (LC-SLIAC), based on the linear relationship between the backscatter values and the local incidence angle (LIA) for a given land cover type in the monitored area. Using the combination of CORINE Land Cover and Hansen et al.’s Global Forest Change databases, a wide range of different LIAs for a specific forest type can be generated for each scene. The algorithm was developed and tested in the cloud-based platform Google Earth Engine (GEE) using Sentinel-1 open access data, Shuttle Radar Topography Mission (SRTM) digital elevation model, and CORINE Land Cover and Hansen et al.’s Global Forest Change databases. The developed method was created primarily for time-series analyses of forests in mountainous areas. LC-SLIAC was tested in 16 study areas over several protected areas in Central Europe. The results after correction by LC-SLIAC showed a reduction of variance and range of backscatter values. Statistically significant reduction in variance (of more than 40%) was achieved in areas with LIA range >50° and LIA interquartile range (IQR) >12°, while in areas with low LIA range and LIA IQR, the decrease in variance was very low and statistically not significant. Six case studies with different LIA ranges were further analyzed in pre- and post-correction time series. Time-series after the correction showed a reduced fluctuation of backscatter values caused by different LIAs in each acquisition path. This reduction was statistically significant (with up to 95% reduction of variance) in areas with a difference in LIA greater than or equal to 27°. LC-SLIAC is freely available on GitHub and GEE, making the method accessible to the wide remote sensing community.
Evaluation of Fengyun-4A Lightning Mapping Imager (LMI) Performance during Multiple Convective Episodes over Beijing
Authors: Chen Zhixiong , Qie Xiushu , Sun Juanzhen , Xiao Xian , Zhang Yuxin , Cao Dongjie , Yang Jing
Published: April 2021

This study investigates the characteristics of space-borne Lightning Mapping Imager (LMI) lightning products and their relationships with cloud properties using ground-based total lightning observations from the Beijing Broadband Lightning Network (BLNET) and cloud information from S-band Doppler radar data. LMI showed generally consistent lightning spatial distributions with those of BLNET, and yielded a considerable lightning detection capability over regions with complex terrain. The ratios between the LMI events, groups and flashes were approximately 9:3:1, and the number of LMI-detected flashes was roughly one order of magnitude smaller than the number of BLNET-detected flashes. However, in different convective episodes, the LMI detection capability was likely to be affected by cloud properties, especially in strongly electrified convective episodes associated with frequent lightning discharging and thick cloud depth. As a result, LMI tended to detect lightning flashes located in weaker and shallower cloud portions associated with fewer cloud shielding effects. With reference to the BLNET total lightning data as the ground truth of observation (both intra-cloud lightning and cloud-to-ground lightning flashes), the LMI event-based detection efficiency (DE) was estimated to reach 28% under rational spatiotemporal matching criteria (1.5 s and 65 km) over Beijing. In terms of LMI flash-based DE, it was much reduced compared with event-based DE. The LMI flash-based ranged between 1.5% and 3.5% with 1.5 s and 35–65 km matching scales. For 330 ms and 35 km, the spatiotemporal matching criteria used to evaluate Geostationary Lightning Mapper (GLM), the LMI flash-based DE was smaller (<1%).
Comparison of Crop Trait Retrieval Strategies Using UAV-Based VNIR Hyperspectral Imaging
Authors: Abdelbaki Asmaa , Schlerf Martin , Retzlaff Rebecca , Machwitz Miriam , Verrelst Jochem , Udelhoven Thomas
Published: April 2021

Hyperspectral cameras onboard unmanned aerial vehicles (UAVs) have recently emerged for monitoring crop traits at the sub-field scale. Different physical, statistical, and hybrid methods for crop trait retrieval have been developed. However, spectra collected from UAVs can be confounded by various issues, including illumination variation throughout the crop growing season, the effect of which on the retrieval performance is not well understood at present. In this study, four retrieval methods are compared, in terms of retrieving the leaf area index (LAI), fractional vegetation cover (fCover), and canopy chlorophyll content (CCC) of potato plants over an agricultural field for six dates during the growing season. We analyzed: (1) The standard look-up table method (LUTstd), (2) an improved (regularized) LUT method that involves variable correlation (LUTreg), (3) hybrid methods, and (4) random forest regression without (RF) and with (RFexp) the exposure time as an additional explanatory variable. The Soil–Leaf–Canopy (SLC) model was used in association with the LUT-based inversion and hybrid methods, while the statistical modelling methods (RF and RFexp) relied entirely on in situ data. The results revealed that RFexp was the best-performing method, yielding the highest accuracies, in terms of the normalized root mean square error (NRMSE), for LAI (5.36%), fCover (5.87%), and CCC (15.01%). RFexp was able to reduce the effects of illumination variability and cloud shadows. LUTreg outperformed the other two retrieval methods (hybrid methods and LUTstd), with an NRMSE of 9.18% for LAI, 10.46% for fCover, and 12.16% for CCC. Conversely, LUTreg led to lower accuracies than those derived from RF for LAI (5.51%) and for fCover (6.23%), but not for CCC (16.21%). Therefore, the machine learning approaches—in particular, RF—appear to be the most promising retrieval methods for application to UAV-based hyperspectral data.
Errors of Airborne Bathymetry LiDAR Detection Caused by Ocean Waves and Dimension-Based Laser Incidence Correction
Authors: Guo Kai , Li Qingquan , Mao Qingzhou , Wang Chisheng , Zhu Jiasong , Liu Yanxiong , Xu Wenxue , Zhang Dejin , Wu Anlei
Published: April 2021

Ocean waves are a vital environmental factor that affects the accuracy of airborne laser bathymetry (ALB) systems. As the regional water surface undulates with randomness, the laser propagation direction through the air–water surface will change and impact the underwater topographic result from the ALB system, especially for the small laser divergence system. However, the natural ocean surface changes rapidly over time, and uneven ocean surface point clouds from ALB scanning will cause an uncertain estimation of the laser propagation direction; therefore, a self-adaptive correction method based on the characteristics of the partial wave surface is key to improving the accuracy and applicability of the ALB system. In this paper, we focused on the issues of spatial position deviation caused by surface waves and position correction of the underwater laser footprint, and the dimension-based adaptive method is applied to attempt to correct the laser incidence angle. Simulation experiments and analysis of the actual measurement data from different ALB systems verified that the method can effectively suppress the influence of ocean waves. Furthermore, the inversion result of sea surface inclination changes is consistent with the surface wind wave reanalysis products. Based on the laser underwater propagation model in the strategy, we also quantitatively analyzed the influence of surface waves on laser bathymetry, which can guide the operation selection and data processing of the ALB system at specific water depths and under dynamic ocean conditions.
Assessment of Land Degradation in Semiarid Tanzania—Using Multiscale Remote Sensing Datasets to Support Sustainable Development Goal 15.3
Authors: Reith Jonathan , Ghazaryan Gohar , Muthoni Francis , Dubovyk Olena
Published: April 2021

Monitoring land degradation (LD) to improve the measurement of the sustainable development goal (SDG) 15.3.1 indicator (“proportion of land that is degraded over a total land area”) is key to ensure a more sustainable future. Current frameworks rely on default medium-resolution remote sensing datasets available to assess LD and cannot identify subtle changes at the sub-national scale. This study is the first to adapt local datasets in interplay with high-resolution imagery to monitor the extent of LD in the semiarid Kiteto and Kongwa (KK) districts of Tanzania from 2000–2019. It incorporates freely available datasets such as Landsat time series and customized land cover and uses open-source software and cloud-computing. Further, we compared our results of the LD assessment based on the adopted high-resolution data and methodology (AM) with the default medium-resolution data and methodology (DM) suggested by the United Nations Convention to Combat Desertification. According to AM, 16% of the area in KK districts was degraded during 2000–2015, whereas DM revealed total LD on 70% of the area. Furthermore, based on the AM, overall, 27% of the land was degraded from 2000–2019. To achieve LD neutrality until 2030, spatial planning should focus on hotspot areas and implement sustainable land management practices based on these fine resolution results.
Coherent Integration Loss Due to Nonstationary Phase Noise in High-Resolution Millimeter-Wave Radars
Authors: Levy Chagai , Pinchas Monika , Pinhasi Yosef
Published: April 2021

Phase noise refers to the instability of an oscillator, which is the cause of instantaneous phase and frequency deviations in the carrier wave. This unavoidable instability adversely affects the performance of range–velocity radar systems, including synthetic aperture radars (SARs) and ground-moving target indicator (GMTI) radars. Phase noise effects should be considered in high-resolution radar designs, operating in millimeter wavelengths and terahertz frequencies, due to their role in radar capability during the reliable identification of target location and velocity. In general, phase noise is a random process consisting of nonstationary terms. It has been shown that in order to optimize the coherent detection of stealthy, fast-moving targets with a low radar cross-section (RCS), it is required to evaluate the integration gain and to determine the incoherent noise effects for resolving target location and velocity. Here, we present an analytical expression for the coherent integration loss when a nonstationary phase noise is considered. A Wigner distribution was employed to derive the time–frequency expression for the coherent loss when nonstationary conditions were considered. Up to now, no analytical expressions have been developed for coherent integration loss when dealing with real nonstationary phase noise mathematical models. The proposed expression will help radar systems estimate the nonstationary integration loss and adjust the decision threshold value in order to maximize the probability of detection. The effect of nonstationary phase noise is demonstrated for studying coherent integration loss of high-resolution radar operating in the W-band. The investigation indicates that major degradation in the time-frequency coherent integration due to short-term, nonstationary phase noise instabilities arises for targets moving at low velocities and increases with range. Opposed to the conventional model, which assumes stationarity, a significant difference of up to 25 dB is revealed in the integration loss for radars operating in the millimeter wave regime. Moreover, for supersonic moving targets, the loss peaks at intermediate distances and then reduces as the target moves away.
Damage Localization and Severity Assessment of a Cable-Stayed Bridge Using a Message Passing Neural Network
Authors: Son Hyesook , Pham Van-Thanh , Jang Yun , Kim Seung-Eock
Published: April 2021

Cable-stayed bridges are damaged by multiple factors such as natural disasters, weather, and vehicle load. In particular, if the stayed cable, which is an essential and weak component of the cable-stayed bridge, is damaged, it may adversely affect the adjacent cables and worsen the bridge structure condition. Therefore, we must accurately determine the condition of the cable with a technology-based evaluation strategy. In this paper, we propose a deep learning model that allows us to locate the damaged cable and estimate its cross-sectional area. To obtain the data required for the deep learning training, we use the tension data of the reduced area cable, which are simulated in the Practical Advanced Analysis Program (PAAP), a robust structural analysis program. We represent the sensor data of the damaged cable-stayed bridge as a graph composed of vertices and edges using tension and spatial information of the sensors. We apply the sensor geometry by mapping the tension data to the graph vertices and the connection relationship between sensors to the graph edges. We employ a Graph Neural Network (GNN) to use the graph representation of the sensor data directly. GNN, which has been actively studied recently, can treat graph-structured data with the most advanced performance. We train the GNN framework, the Message Passing Neural Network (MPNN), to perform two tasks to identify damaged cables and estimate the cable areas. We adopt a multi-task learning method for more efficient optimization. We show that the proposed technique achieves high performance with the cable-stayed bridge data generated from PAAP.
A Colorimetric Dip Strip Assay for Detection of Low Concentrations of Phosphate in Seawater
Authors: Heidari-Bafroui Hojat , Charbaji Amer , Anagnostopoulos Constantine , Faghri Mohammad
Published: April 2021

Nutrient pollution remains one of the greatest threats to water quality and imposes numerous public health and ecological concerns. Phosphate, the most common form of phosphorus, is one of the key nutrients necessary for plant growth. However, phosphate concentration in water should be carefully monitored for environmental protection requirements. Hence, an easy-to-use, field-deployable, and reliable device is needed to measure phosphate concentrations in the field. In this study, an inexpensive dip strip is developed for the detection of low concentrations of phosphate in water and seawater. In this device, ascorbic acid/antimony reagent was dried on blotting paper, which served as the detection zone, and was followed by a wet chemistry protocol using the molybdenum method. Ammonium molybdate and sulfuric acid were separately stored in liquid form to significantly improve the lifetime of the device and enhance the reproducibility of its performance. The device was tested with deionized water and Sargasso Sea seawater. The limits of detection and quantification for the optimized device using a desktop scanner were 0.134 ppm and 0.472 ppm for phosphate in water and 0.438 ppm and 1.961 ppm in seawater, respectively. The use of the portable infrared lightbox previously developed at our lab improved the limits of detection and quantification by a factor of three and were 0.156 ppm and 0.769 ppm for the Sargasso Sea seawater. The device’s shelf life, storage conditions, and limit of detection are superior to what was previously reported for the paper-based phosphate detection devices.
Variable Link Performance Due to Weather Effects in a Long-Range, Low-Power LoRa Sensor Network
Authors: Ameloot Thomas , Van Torre Patrick , Rogier Hendrik
Published: April 2021

When aiming for the wider deployment of low-power sensor networks, the use of sub-GHz frequency bands shows a lot of promise in terms of robustness and minimal power consumption. Yet, when deploying such sensor networks over larger areas, the link quality can be impacted by a host of factors. Therefore, this contribution demonstrates the performance of several links in a real-world, research-oriented sensor network deployed in a (sub)urban environment. Several link characteristics are presented and analysed, exposing frequent signal deterioration and, more rarely, signal strength enhancement along certain long-distance wireless links. A connection is made between received power levels and seasonal weather changes and events. The irregular link performance presented in this paper is found to be genuinely disruptive when pushing sensor-networks to their limits in terms of range and power use. This work aims to give an indication of the severity of these effects in order to enable the design of truly reliable sensor networks.