bluuebunny/crossref_metadata_2025 huggingface dataset:
Natural Rubber Biocomposites Filled with Phyto-Ashes Rich in Biogenic Silica Obtained from Wheat Straw and Field Horsetail
Authors: Masłowski Marcin , Miedzianowska Justyna , Delekta Maciej , Czylkowska Agnieszka , Strzelec Krzysztof
Published: April 2021

The rich structural hierarchy of plants permits the obtainment of porous structures which can be expected to show improved performances in fields such as pharmaceuticals and cosmetics, catalysis, drug delivery, adsorption, separation or sensors in various chemical reactions. On the other hand, porous materials can be an active additive to polymer composites. The aim of the study was to obtain natural rubber (NR) biocomposites with the addition of phyto-ashes reach in biogenic silica from plant biomass. For the production of bioadditives, a two-stage method of high-temperature heat treatment was used, preceded by acid hydrolysis of plant tissues in the form of horsetail and wheat straw. Hydrolysis was performed with hydrochloric and citric acid. The efficiency of the processes and their influence on the elemental composition, surface morphology, thermal stability and particle size of the fillers were determined. Modified bioadditives were introduced into the elastomer matrix and their processing properties, as well as the vulcanization characteristics, were examined. Static mechanical properties (tensile strength, elongation at break, stress at 100%, 200% and 300% elongation), dynamic-mechanical analysis and the influence of additives on the cross-link density of the composites were determined. Structural analysis was performed using scanning electron microscopy. It was found that the field horsetail and cereal straw are plants rich in many valuable chemical compounds, especially silica. The specific and appropriate treatment of these plants can lead to bioadditives that significantly affect the properties of rubber materials.
Mechanical Testing and Modeling of the Time–Temperature Superposition Response in Hybrid Fiber Reinforced Composites
Authors: Koutsomichalis Aggelos , Kalampoukas Thomas , Mouzakis Dionysios E.
Published: April 2021

The purpose of this study was to manufacture hybrid composites from fabrics with superior ballistic performance, and to analyze their viscoelastic and mechanical response. Therefore, composites in hybrid lay-up modes were manufactured from Vectran, Kevlar and aluminum fiber-woven fabrics through a vacuum assisted resin transfer molding. The specimens were consequently analyzed using static three-point bending, as well as by dynamic mechanical analysis (DMA). Apart from DMA, time–temperature superposition (TTS) analysis was performed by all available models. It was possible to study the intrinsic viscoelastic behavior of hybrid ballistic laminates, with TTS analysis gained from creep testing. A polynomic mathematical function was proposed to provide a high accuracy for TTS curves, when shifting out of the linearity regimes is required. The usual Williams–Landel–Ferry and Arrhenius models proved not useful in order to describe and model the shift factors of the acquired curves. In terms of static results, the highly nonlinear stress–strain curve of both composites was obvious, whereas the differential mechanism of failure in relation to stress absorption, at each stage of deformation, was studied. SEM fractography revealed that hybrid specimens with Kevlar plies are prone to tensile side failure, whereas the hybrid specimens with Vectran plies exhibited high performance on the tensile side of the specimens in three-point bending, leading to compressive failure owing to the high stress retained at higher strains after the maximum bending strength was reached.
Effect of Chitosan and Aloe Vera Extract Concentrations on the Physicochemical Properties of Chitosan Biofilms
Authors: Yoshida Cristiana M. P. , Pacheco Murilo S. , de Moraes Mariana A. , Lopes Patrícia S. , Severino Patrícia , Souto Eliana B. , da Silva Classius F.
Published: April 2021

Chitosan films have been extensively studied as dressings in formulations for the treatment of chronic wounds. The incorporation of aloe vera (Aloe barbadensis Miller) into chitosan dressings could potentialize the healing process since aloe vera shows several pharmacological activities. This work aimed to evaluate the effect of aloe vera and chitosan concentrations on the physicochemical properties of the developed films. The films were obtained by casting technique and characterized with respect to their color parameters, morphology, barrier and mechanical properties, and thermal analysis. Results showed that the presence of aloe vera modified the films′ color parameters, changed barrier properties, increased fluid handling capacity (FHC), and decreased water-vapor permeability (WVP). The reduced elongation at break resulted in more rigid films. Aloe vera concentration did not significantly change film properties, but the presence of this gel increased the films’ stability at temperatures below 200 °C, showing similar behavior as chitosan films above 400 °C. The results suggest a crosslinking/complexation between chitosan and aloe vera, which combine appropriate physicochemical properties for application as wound dressing materials.
Use of Extended Cover Factor Theory in UV Protection of Woven Fabric
Authors: Kostajnšek Klara , Dimitrovski Krste
Published: April 2021

The paper presents an extension of existed cover factor theory more suitable for the evaluation of light penetration through a net woven fabrics structure. It also introduces a new simplified model of predicting the ultraviolet (UV) protective properties of woven fabrics assuming that the coefficient of reflection (KR), transmission (KT), and absorption (KA) of constitutive yarns are known. Since usually they are not, the procedure of preparation of simulation of proper woven fabric samples without interlacing and with known constructional parameters is also presented. The procedure finishes with a fast and cheap detection of missed coefficient for any type of yarns. There are differences between theoretical and measured results, which are not particularly significant in regard to the purpose and demands of investigation.
Influence of the Glass Transition Temperature and the Density of Crosslinking Groups on the Reversibility of Diels-Alder Polymer Networks
Authors: Thiessen Merlina , Abetz Volker
Published: April 2021

The interest in self-healing, recyclable, and adaptable polymers is growing. This work addresses the reversibility of crosslink formation based on Diels-Alder reaction in copolymer networks containing furfuryl and maleimide groups, which represent the “diene” and the “dienophile,” respectively. The copolymers are synthesized by atom transfer radical polymerization (ATRP) and free radical polymerization. The diene bearing copolymers are crosslinked either with a small molecule containing two dienophiles or with a dienophile bearing copolymer. The influence of the crosslinking temperature on the Diels-Alder reaction is analyzed. Furthermore, the influence of the glass transition temperature and the influence of the density of crosslinking groups on the thermo-reversibility of crosslinking are investigated by temperature dependent infrared spectroscopy and differential scanning calorimetry. It is shown that the reversibility of crosslinking is strongly influenced by the glass transition temperature of the system.
Development and Investigation of PEDOT:PSS Composition Coated Fabrics Intended for Microwave Shielding and Absorption
Authors: Rubeziene Vitalija , Baltusnikaite-Guzaitiene Julija , Abraitiene Ausra , Sankauskaite Audrone , Ragulis Paulius , Santos Gilda , Pimenta Juana
Published: April 2021

This study presents the investigation of the electromagnetic properties and resistance performance of electrically conductive fabrics coated with composition containing the conjugated polymer system poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS). The developed fabrics were intended for electromagnetic radiation (EMR) shielding in microwave range and for absorbing microwaves in radar operating range, so as to act as radar absorbing materials (RAM). The measurements of reflection and transmission of the developed fabrics were performed in a frequency range of 2–18 GHz, which covers the defined frequencies relevant to the application. Four types of fabrics with different fiber composition (polyamide; polyamide/cotton; wool and para-aramid/viscose) were selected and coated with conductive paste using screen printing method. It was found that EMR shielding effectiveness (SE) as well as absorption properties depend not only the amount of conductive paste topped on the fabric, but also resides in the construction parameters of fabrics. Depending on such fabric structural parameters as density, mass per unit area, type of weave, a layer of shield (or coating) just sticks on the fabric surface or penetrates into fabric, changing the shield thickness and herewith turning SE results. Meanwhile, the fiber composition of fabrics influences mostly bonding between fibers and polymer coating. To improve the resistance performance of the developed samples, a conventional textile surface modification technique, atmospheric plasma treatment, was applied. Initially, before plasma treatment and after treatment the fabrics were evaluated regarding an aqueous liquid repellency test, measuring the contact angles for the water solvent. The influence of plasma treatment on resistance performance of coated fabrics was evaluated by subjecting the plasma treated samples and untreated samples to abrasion in the Martindale abrasion apparatus and to multiplex washing cycles. These investigations revealed that applied plasma treatment visibly improved abrasion resistance as a result of better adhesion of the coating. However, washing resistance increased not so considerably.
Structure Design of GFRP Composite Leaf Spring: An Experimental and Finite Element Analysis
Authors: Ma Linlin , He Jingwu , Gu Yizhuo , Zhang Zuoguang , Yu Zechuan , Zhou Ao , Tam Lik-ho , Wu Chao
Published: April 2021

Due to the high load-bearing capacity and light weight, composite leaf spring with variable width and variable thickness has been increasingly used in the automobile industry to replace the conventional steel leaf spring with a heavy weight. The optimum structural design of composite leaf spring is particularly favorable for the weight reduction. In this study, an effective algorithm is developed for structural optimization of composite leaf spring. The mechanical performance of composite leaf spring with designed dimensions is characterized using a combined experimental and computational approach. Specifically, the composite leaf spring with variable width and variable thickness was prepared using the filament winding process, and the three-dimensional finite element (FE) model of the designed composite leaf spring is developed. The experimental sample and FE model of composite leaf spring are tested under the three-point bending method. From experimental and simulation results, it is shown that the bending stiffness of the designed leaf spring meets the design requirement in the automotive industry, while the results of stress calculation along all directions meet the requirements of material strength requirement. The developed algorithm contributes to the design method for optimizing the stiffness and strength performance of the composite leaf spring.
The Versatility of Polymeric Materials as Self-Healing Agents for Various Types of Applications: A Review
Authors: Nik Md Noordin Kahar Nik Nur Farisha , Osman Azlin Fazlina , Alosime Eid , Arsat Najihah , Mohammad Azman Nurul Aida , Syamsir Agusril , Itam Zarina , Abdul Hamid Zuratul Ain
Published: April 2021

The versatility of polymeric materials as healing agents to prevent any structure failure and their ability to restore their initial mechanical properties has attracted interest from many researchers. Various applications of the self-healing polymeric materials are explored in this paper. The mechanism of self-healing, which includes the extrinsic and intrinsic approaches for each of the applications, is examined. The extrinsic mechanism involves the introduction of external healing agents such as microcapsules and vascular networks into the system. Meanwhile, the intrinsic mechanism refers to the inherent reversibility of the molecular interaction of the polymer matrix, which is triggered by the external stimuli. Both self-healing mechanisms have shown a significant impact on the cracked properties of the damaged sites. This paper also presents the different types of self-healing polymeric materials applied in various applications, which include electronics, coating, aerospace, medicals, and construction fields. It is expected that this review gives a significantly broader idea of self-healing polymeric materials and their healing mechanisms in various types of applications.
UV-Light Curing of 3D Printing Inks from Vegetable Oils for Stereolithography
Authors: Barkane Anda , Platnieks Oskars , Jurinovs Maksims , Kasetaite Sigita , Ostrauskaite Jolita , Gaidukovs Sergejs , Habibi Youssef
Published: April 2021

Typical resins for UV-assisted additive manufacturing (AM) are prepared from petroleum-based materials and therefore do not contribute to the growing AM industry trend of converting to sustainable bio-based materials. To satisfy society and industry’s demand for sustainability, renewable feedstocks must be explored; unfortunately, there are not many options that are applicable to photopolymerization. Nevertheless, some vegetable oils can be modified to be suitable for UV-assisted AM technologies. In this work, extended study, through FTIR and photorheology measurements, of the UV-curing of epoxidized acrylate from soybean oil (AESO)-based formulations has been performed to better understand the photopolymerization process. The study demonstrates that the addition of appropriate functional comonomers like trimethylolpropane triacrylate (TMPTA) and the adjusting of the concentration of photoinitiator from 1% to 7% decrease the needed UV-irradiation time by up to 25%. Under optimized conditions, the optimal curing time was about 4 s, leading to a double bond conversion rate (DBC%) up to 80% and higher crosslinking density determined by the Flory–Rehner empirical approach. Thermal and mechanical properties were also investigated via TGA and DMA measurements that showed significant improvements of mechanical performances for all formulations. The properties were improved further upon the addition of the reactive diluents. After the thorough investigations, the prepared vegetable oil-based resin ink formulations containing reactive diluents were deemed suitable inks for UV-assisted AM, giving their appropriate viscosity. The validation was done by printing different objects with complex structures using a laser based stereolithography apparatus (SLA) printer.
Religion and Theatrical Drama, an Introduction
Authors: Bouchard Larry D. , Gillespie Charles A.
Published: April 2021

Often, a lonely light bulb illuminates the edge of a stage outside of working hours [...]
NRTK, PPP or Static, That Is the Question. Testing Different Positioning Solutions for GNSS Survey
Authors: Dardanelli Gino , Maltese Antonino , Pipitone Claudia , Pisciotta Alessandro , Lo Brutto Mauro
Published: April 2021

Worldwide, the determination of the coordinates from a Global Navigation Satellite System (GNSS) survey (in Network Real Time Kinematic, Precise Point Positioning, or static mode) has been analysed in several scientific and technical applications. Many of those have been carried out to compare Precise Point Positioning (PPP), Network Real Time Kinematic (NRTK), and static modes’ solutions, usually, using the latter as the true or the most plausible solution. This approach is not always possible as the static mode solution depends on several parameters (baseline length, acquisition time, ionospheric, and tropospheric models, etc.) that must be considered to evaluate the accuracy of the method. This work aims to show the comparison among the GNSS survey methods mentioned above, using some benchmark points. The tests were carried out by comparing the survey methods in pairs to check their solutions congruence. The NRTK and the static solutions refer to a local GNSS CORS network’s analysis. The NRTK positioning has been obtained with different methods (VRS, FKP, NEA) and the PPP solution has been calculated with two different software (RTKLIB and CSRS-PPP). A statistical approach has been performed to check if the distribution frequencies of the coordinate’s residual belong to the normal distribution, for all pairs analysed. The results show that the hypothesis of a normal distribution is confirmed in most of the pairs and, specifically, the Static vs. NRTK pair seems to achieve the best congruence, while involving the PPP approach, pairs obtained with CSRS software achieve better congruence than those involving RTKLIB software.
Effect of Ecological Construction Engineering on Vegetation Restoration: A Case Study of the Loess Plateau
Authors: Xiu Lina , Yao Xiaojun , Chen Mengdie , Yan Changzhen
Published: April 2021

Since the 1980s, with rapid economic development and increased attention given to ecological protection, China has launched a series of ecological-restoration programs to restore the local environment through afforestation and natural forest protection. The evaluation of vegetation restoration is an important part of evaluating the effectiveness of ecological restoration. The Loess Plateau is an area where ecological problems are concentrated, and it is a key area of ecological construction in China. This paper takes the Loess Plateau as the research area, using remote sensing and geographic information technology combined with ecosystem structural changes and an improved residual model to study vegetation restoration. The following main conclusions were drawn: (1) From 1990 to 2000, the farmland area increased by 3084.81 km2, resulting in the encroachment of a large area of grassland and shrubland. (2) With the implementation of ecological engineering, the area of returning farmland to forest and grassland reached 18,001.88 km2; in this period, the NDVI of vegetation increased rapidly, and the area that increased comprised 91.90% of the total area, of which the area of significant increase reached 65.78%. The quality of vegetation was restored to a great extent, and ecological engineering played a major role in this stage. (3) Under the background of large-scale implementation of ecological restoration, the urban area of the Loess Plateau continues to expand.
Spotting Green Tides over Brittany from Space: Three Decades of Monitoring with Landsat Imagery
Authors: Schreyers Louise , van Emmerik Tim , Biermann Lauren , Le Lay Yves-François
Published: April 2021

Green tides of macroalgae have been negatively affecting the coasts of Brittany, France, for at least five decades, caused by excessive nitrogen inputs from the farming sector. Regular areal estimates of green tide surfaces are publicly available but only from 2002 onwards. Using free and openly accessible Landsat satellite imagery archives over 35 years (1984–2019), this study explores the potential of remote sensing for detection and long-term monitoring of green macroalgae blooms. By using a Google Earth Engine (GEE) script, we were able to detect and quantify green tide surfaces using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) at four highly affected beaches in Northern Brittany. Mean green tide coverage was derived and analyzed from 1984 to 2019, at both monthly and annual scales. Our results show important interannual and seasonal fluctuations in estimated macroalgae cover. In terms of trends over time, green tide events did not show a decrease in extent at three out of four studied sites. The observed decrease in nitrogen concentrations for the rivers draining the study sites has not resulted in a reduction of green tide extents.
Estimating Water Vapor Using Signals from Microwave Links below 25 GHz
Authors: Song Kun , Liu Xichuan , Gao Taichang , Zhang Peng
Published: April 2021

Water vapor is a key element in both the greenhouse effect and the water cycle. However, water vapor has not been well studied due to the limitations of conventional monitoring instruments. Recently, estimating rain rate by the rain-induced attenuation of commercial microwave links (MLs) has been proven to be a feasible method. Similar to rainfall, water vapor also attenuates the energy of MLs. Thus, MLs also have the potential of estimating water vapor. This study proposes a method to estimate water vapor density by using the received signal level (RSL) of MLs at 15, 18, and 23 GHz, which is the first attempt to estimate water vapor by MLs below 20 GHz. This method trains a sensing model with prior RSL data and water vapor density by the support vector machine, and the model can directly estimate the water vapor density from the RSLs without preprocessing. The results show that the measurement resolution of the proposed method is less than 1 g/m3. The correlation coefficients between automatic weather stations and MLs range from 0.72 to 0.81, and the root mean square errors range from 1.57 to 2.31 g/m3. With the large availability of signal measurements from communications operators, this method has the potential of providing refined data on water vapor density, which can contribute to research on the atmospheric boundary layer and numerical weather forecasting.
Sensor Agnostic Semantic Segmentation of Structurally Diverse and Complex Forest Point Clouds Using Deep Learning
Authors: Krisanski Sean , Taskhiri Mohammad Sadegh , Gonzalez Aracil Susana , Herries David , Turner Paul
Published: April 2021

Forest inventories play an important role in enabling informed decisions to be made for the management and conservation of forest resources; however, the process of collecting inventory information is laborious. Despite advancements in mapping technologies allowing forests to be digitized in finer granularity than ever before, it is still common for forest measurements to be collected using simple tools such as calipers, measuring tapes, and hypsometers. Dense understory vegetation and complex forest structures can present substantial challenges to point cloud processing tools, often leading to erroneous measurements, and making them of less utility in complex forests. To address this challenge, this research demonstrates an effective deep learning approach for semantically segmenting high-resolution forest point clouds from multiple different sensing systems in diverse forest conditions. Seven diverse point cloud datasets were manually segmented to train and evaluate this model, resulting in per-class segmentation accuracies of Terrain: 95.92%, Vegetation: 96.02%, Coarse Woody Debris: 54.98%, and Stem: 96.09%. By exploiting the segmented point cloud, we also present a method of extracting a Digital Terrain Model (DTM) from such segmented point clouds. This approach was applied to a set of six point clouds that were made publicly available as part of a benchmarking study to evaluate the DTM performance. The mean DTM error was 0.04 m relative to the reference with 99.9% completeness. These approaches serve as useful steps toward a fully automated and reliable measurement extraction tool, agnostic to the sensing technology used or the complexity of the forest, provided that the point cloud has sufficient coverage and accuracy. Ongoing work will see these models incorporated into a fully automated forest measurement tool for the extraction of structural metrics for applications in forestry, conservation, and research.
A Model-Driven-to-Sample-Driven Method for Rural Road Extraction
Authors: Dai Jiguang , Ma Rongchen , Gong Litao , Shen Zimo , Wu Jialin
Published: April 2021

Road extraction in rural areas is one of the most fundamental tasks in the practical application of remote sensing. In recent years, sample-driven methods have achieved state-of-the-art performance in road extraction tasks. However, sample-driven methods are prohibitively expensive and laborious, especially when dealing with rural roads with irregular curvature changes, narrow widths, and diverse materials. The template matching method can overcome these difficulties to some extent and achieve impressive road extraction results. This method also has the advantage of the vectorization of road extraction results, but the automation is limited. Straight line sequences can be substituted for curves, and the use of the color space can increase the recognition of roads and nonroads. A model-driven-to-sample-driven road extraction method for rural areas with a much higher degree of automation than existing template matching methods is proposed in this study. Without prior samples, on the basis of the geometric characteristics of narrow and long roads and using the advantages of straight lines instead of curved lines, the road center point extraction model is established through length constraints and gray mean contrast constraints of line sequences, and the extraction of some rural roads is completed through topological connection analysis. In addition, we take the extracted road center point and manual input data as local samples, use the improved line segment histogram to determine the local road direction, and use the panchromatic and hue, saturation, value (HSV) space interactive matching model as the matching measure to complete the road tracking extraction. Experimental results show that, for different types of data and scenarios on the premise, the accuracy and recall rate of the evaluation indicators reach more than 98%, and, compared with other methods, the automation of this algorithm has increased by more than 40%.
Retrieving and Validating Leaf and Canopy Chlorophyll Content at Moderate Resolution: A Multiscale Analysis with the Sentinel-3 OLCI Sensor
Authors: De Grave Charlotte , Pipia Luca , Siegmann Bastian , Morcillo-Pallarés Pablo , Rivera-Caicedo Juan Pablo , Moreno José , Verrelst Jochem
Published: April 2021

ESA’s Eighth Earth Explorer mission “FLuorescence EXplorer” (FLEX) will be dedicated to the global monitoring of the chlorophyll fluorescence emitted by vegetation. In order to properly interpret the measured fluorescence signal, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem formation with Sentinel-3 (S3), which conveys the Ocean and Land Color Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In support of FLEX’s preparatory activities, this paper presents a first validation exercise of OLCI vegetation products against in situ data coming from the 2018 FLEXSense campaign. During this campaign, leaf chlorophyll content (LCC) and leaf area index (LAI) measurements were collected over croplands, while HyPlant DUAL images of the area were acquired at a 3 m spatial resolution. A multiscale validation strategy was pursued. First, estimates of these two variables, together with the combined canopy chlorophyll content (CCC = LCC × LAI), were obtained at the HyPlant spatial resolution and were compared against the in situ measurements. Second, the fine-scale retrieval maps from HyPlant were coarsened to the S3 spatial scale as a reference to assess the quality of the OLCI vegetation products. As an intermediary step, vegetation products extracted from Sentinel-2 data were used to compare retrievals at the in-between spatial resolution of 20 m. For all spatial scales, CCC delivered the most accurate estimates with the smallest prediction error obtained at the 300 m resolution (R2 of 0.74 and RMSE = 26.8 μg cm−2). Results of a scaling analysis suggest that CCC performs well at the different tested spatial resolutions since it presents a linear behavior across scales. LCC, on the other hand, was poorly retrieved at the 300 m scale, showing overestimated values over heterogeneous pixels. The introduction of a new LCC model integrating mixed reflectance spectra in its training enabled to improve by 16% the retrieval accuracy for this variable (RMSE = 10 μg cm−2 for the new model versus RMSE = 11.9 μg cm−2 for the former model).
Observations of Wintertime Low-Level Jets in the Coastal Region of the Laptev Sea in the Siberian Arctic Using SODAR/RASS
Authors: Heinemann Günther , Drüe Clemens , Schwarz Pascal , Makshtas Alexander
Published: April 2021

In 2014/2015 a one-year field campaign at the Tiksi observatory in the Laptev Sea area was carried out using Sound Detection and Ranging/Radio Acoustic Sounding System (SODAR/RASS) measurements to investigate the atmospheric boundary layer (ABL) with a focus on low-level jets (LLJ) during the winter season. In addition to SODAR/RASS-derived vertical profiles of temperature, wind speed and direction, a suite of complementary measurements at the Tiksi observatory was available. Data of a regional atmospheric model were used to put the local data into the synoptic context. Two case studies of LLJ events are presented. The statistics of LLJs for six months show that in about 23% of all profiles LLJs were present with a mean jet speed and height of about 7 m/s and 240 m, respectively. In 3.4% of all profiles LLJs exceeding 10 m/s occurred. The main driving mechanism for LLJs seems to be the baroclinicity, since no inertial oscillations were found. LLJs with heights below 200 m are likely influenced by local topography.
Applications of Satellite Radar Imagery for Hazard Monitoring: Insights from Australia
Authors: Parker Amy L. , Castellazzi Pascal , Fuhrmann Thomas , Garthwaite Matthew C. , Featherstone Will E.
Published: April 2021

Earth observation (EO) satellites facilitate hazard monitoring and mapping over large-scale and remote areas. Despite Synthetic Aperture Radar (SAR) satellites being well-documented as a hazard monitoring tool, the uptake of these data is geographically variable, with the Australian continent being one example where the use of SAR data is limited. Consequently, less is known about how these data apply in the Australian context, how they could aid national hazard monitoring and assessment, and what new insights could be gleaned for the benefit of the international disaster risk reduction community. The European Space Agency Sentinel-1 satellite mission now provides the first spatially and temporally complete global SAR dataset and the first opportunity to use these data to systematically assess hazards in new locations. Using the example of Australia, where floods and uncontrolled bushfires, earthquakes, resource extraction (groundwater, mining, hydrocarbons) and geomorphological changes each pose potential risks to communities, we review past usage of EO for hazard monitoring and present a suite of new case studies that demonstrate the potential added benefits of SAR. The outcomes provide a baseline understanding of the potential role of SAR in national hazard monitoring and assessment in an Australian context. Future opportunities to improve national hazard identification will arise from: new SAR sensing capabilities, which for Australia includes a first-ever civilian EO capability, NovaSAR-1; the integration of Sentinel-1 SAR with other EO datasets; and the provision of standardised SAR products via Analysis Ready Data and Open Data Cubes to support operational applications.
Ambient PM2.5 Estimates and Variations during COVID-19 Pandemic in the Yangtze River Delta Using Machine Learning and Big Data
Authors: Lu Debin , Mao Wanliu , Zheng Lilin , Xiao Wu , Zhang Liang , Wei Jing
Published: April 2021

The lockdown of cities in the Yangtze River Delta (YRD) during COVID-19 has provided many natural and typical test sites for estimating the potential of air pollution control and reduction. To evaluate the reduction of PM2.5 concentration in the YRD region by the epidemic lockdown policy, this study employs big data, including PM2.5 observations and 29 independent variables regarding Aerosol Optical Depth (AOD), climate, terrain, population, road density, and Gaode map Point of interesting (POI) data, to build regression models and retrieve spatially continuous distributions of PM2.5 during COVID-19. Simulation accuracy of multiple machine learning regression models, i.e., random forest (RF), support vector regression (SVR), and artificial neural network (ANN) were compared. The results showed that the RF model outperformed the SVR and ANN models in the inversion of PM2.5 in the YRD region, with the model-fitting and cross-validation coefficients of determination R2 reached 0.917 and 0.691, mean absolute error (MAE) values were 1.026 μg m−3 and 2.353 μg m−3, and root mean square error (RMSE) values were 1.413 μg m−3, and 3.144 μg m−3, respectively. PM2.5 concentrations during COVID-19 in 2020 have decreased by 3.61 μg m−3 compared to that during the same period of 2019 in the YRD region. The results of this study provide a cost-effective method of air pollution exposure assessment and help provide insight into the atmospheric changes under strong government controlling strategies.
Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule
Authors: Terres de Lima Lucas , Fernández-Fernández Sandra , Gonçalves João Francisco , Magalhães Filho Luiz , Bernardes Cristina
Published: April 2021

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.
Predicting Water Stress in Wild Blueberry Fields Using Airborne Visible and Near Infrared Imaging Spectroscopy
Authors: Chan Catherine , Nelson Peter R. , Hayes Daniel J. , Zhang Yong-Jiang , Hall Bruce
Published: April 2021

Water management and irrigation practices are persistent challenges for many agricultural systems, exacerbated by changing seasonal and weather patterns. The wild blueberry industry is at heightened susceptibility due to its unique growing conditions and uncultivated nature. Stress detection in agricultural fields can prompt management responses to mitigate detrimental conditions, including drought and disease. We assessed airborne spectral data accompanied by ground sampled water potential over three developmental stages of wild blueberries collected throughout the 2019 summer on two adjacent fields, one irrigated and one non-irrigated. Ground sampled leaves were collected in tandem to the hyperspectral image collection with an unoccupied aerial vehicle (UAV) and then measured for leaf water potential. Using methods in machine learning and statistical analysis, we developed models to determine irrigation status and water potential. Seven models were assessed in this study, with four used to process six hyperspectral cube images for analysis. These images were classified as irrigated or non-irrigated and estimated for water potential levels, resulting in an R2 of 0.62 and verified with a validation dataset. Further investigation relating imaging spectroscopy and water potential will be beneficial in understanding the dynamics between the two for future studies.
The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems
Authors: Dobler Gregory , Bianco Federica B. , Sharma Mohit S. , Karpf Andreas , Baur Julien , Ghandehari Masoud , Wurtele Jonathan , Koonin Steven E.
Published: April 2021

We describe an “Urban Observatory” facility designed for the study of complex urban systems via persistent, synoptic, and granular imaging of dynamical processes in cities. An initial deployment of the facility has been demonstrated in New York City and consists of a suite of imaging systems—both broadband and hyperspectral—sensitive to wavelengths from the visible (∼400 nm) to the infrared (∼13 micron) operating at cadences of ∼0.01–30 Hz (characteristically ∼0.1 Hz). Much like an astronomical survey, the facility generates a large imaging catalog from which we have extracted observables (e.g., time-dependent brightnesses, spectra, temperatures, chemical species, etc.), collecting them in a parallel source catalog. We have demonstrated that, in addition to the urban science of cities as systems, these data are applicable to a myriad of domain-specific scientific inquiries related to urban functioning including energy consumption and end use, environmental impacts of cities, and patterns of life and public health. We show that an Urban Observatory facility of this type has the potential to improve both a city’s operations and the quality of life of its inhabitants.
Quantifying Hole-Edge Crack of Bolt Joints by Using an Embedding Triangle Eddy Current Sensing Film
Authors: Fan Shilei , Yi Junyan , Sun Hu , Yun Fenglin
Published: April 2021

Hole-edge crack quantification of bolt joints is critical for monitoring and estimating structural integrity of aircraft. The paper proposes a new triangle eddy current sensor array for the purpose of increasing the level of quantifying hole-edge crack parameters, especially, the crack angle. The new senor array consists of triangular coils instead of planar rectangular coils. The configuration of the novel sensor array, including the excitation current directions and the excitation winding shape, is optimized by simulation. The ability of the proposed sensing film to identify the crack parameters has been verified by finite element simulations and experiments. Results shows that triangular coils with same current directions in circumferentially adjacent coils and opposite current directions in axially adjacent coils achieve better performance in sensor linearity and resolution compared to rectangular coils. In addition, it has also been proved that the sensing film has a good potential to identify the crack depth and length.
Response of Transitional Mixtures Retaining Memory of In-Situ Overburden Pressure Monitored Using Electromagnetic and Piezo Crystal Sensors
Authors: Kim Sang Yeob , Lee Jong-Sub , Park Junghee
Published: April 2021

The major and minor components in granular soil materials determine their properties and behavior. This study explores the transitional behavior within threshold fines fraction of soil mixtures based on the data from the literature and experiments. From the literature survey, the void ratio, shear wave velocity, compression index, and friction angle capture the transitional turning point between the low and data-adjusted high threshold fines fractions. In particular, there is a dramatic change in hydraulic conductivity below the low threshold fines fraction that highlights the critical role of small amounts of fines in the fluid flow (e.g., clogging). From an experimental study, the engineering properties of natural soil samples identified using deformation and elastic wave sensors show transitional trends within the Revised Soil Classification System framework. The evolution of compressibility and shear wave velocity indicate that either coarse, fine, or both particles are likely to contribute to large and small strain stiffnesses when the effective stress is below 400 kPa. Thereafter, both engineering properties indicate that the soil sample retains a memory of in-situ overburden pressure when the effective stress is around 400 kPa. There is a critical role of fines that are slightly higher than low threshold fines fraction on engineering properties that promote the application of Revised Soil Classification System RSCS to natural soils.
Biomedical Photoacoustic Imaging and Sensing Using Affordable Resources
Authors: Kuniyil Ajith Singh Mithun , Xia Wenfeng
Published: April 2021

The photoacoustic (PA) effect, also called the optoacoustic effect, was discovered in the 1880s by Alexander Graham Bell and has been utilized for biomedical imaging and sensing applications since the early 1990s [...]
A Comprehensive Comparison and Validation of Published Methods to Detect Turn Switch during Alpine Skiing
Authors: Martínez Aaron , Snyder Cory , Moore Stephanie R. , Stöggl Thomas
Published: April 2021

The instant of turn switch (TS) in alpine skiing has been assessed with a variety of sensors and TS concepts. Despite many published methodologies, it is unclear which is best or how comparable they are. This study aimed to facilitate the process of choosing a TS method by evaluating the accuracy and precision of the methodologies previously used in literature and to assess the influence of the sensor type. Optoelectronic motion capture, inertial measurement units, pressure insoles, portable force plates, and electromyography signals were recorded during indoor treadmill skiing. All TS methodologies were replicated as stated in their respective publications. The method proposed by Supej assessed with optoelectronic motion capture was used as a comparison reference. TS time differences between the reference and each methodology were used to assess accuracy and precision. All the methods analyzed showed an accuracy within 0.25 s, and ten of them within 0.05 s. The precision ranged from ~0.10 s to ~0.60 s. The TS methodologies with the best performance (accuracy and precision) were Klous Video, Spörri PI (pressure insoles), Martinez CTD (connected boot), and Yamagiwa IMU (inertial measurement unit). In the future, the specific TS methodology should be chosen with respect to sensor selection, performance, and intended purpose.
Developing a Modern Greenhouse Scientific Research Facility—A Case Study
Authors: Cafuta Davor , Dodig Ivica , Cesar Ivan , Kramberger Tin
Published: April 2021

Multidisciplinary approaches in science are still rare, especially in completely different fields such as agronomy science and computer science. We aim to create a state-of-the-art floating ebb and flow system greenhouse that can be used in future scientific experiments. The objective is to create a self-sufficient greenhouse with sensors, cloud connectivity, and artificial intelligence for real-time data processing and decision making. We investigated various approaches and proposed an optimal solution that can be used in much future research on plant growth in floating ebb and flow systems. A novel microclimate pocket-detection solution is proposed using an automatically guided suspended platform sensor system. Furthermore, we propose a methodology for replacing sensor data knowledge with artificial intelligence for plant health estimation. Plant health estimation allows longer ebb periods and increases the nutrient level in the final product. With intelligent design and the use of artificial intelligence algorithms, we will reduce the cost of plant research and increase the usability and reliability of research data. Thus, our newly developed greenhouse would be more suitable for plant growth research and production.
Low-Cost Prototype to Automate the 3D Digitization of Pieces: An Application Example and Comparison
Authors: González-Merino Ramón , Sánchez-López Elena , Romero Pablo E. , Rodero Jesús , Hidalgo-Fernández Rafael E.
Published: April 2021

This work is aimed at describing the design of a mechanical and programmable 3D capturing system to be used by either 3D scanner or DSLR camera through photogrammetry. Both methods are widely used in diverse areas, from engineering, architecture or archaeology, up to the field of medicine; but they also entail certain disadvantages, such as the high costs of certain equipment, such as scanners with some precision, and the need to resort to specialized operatives, among others. The purpose of this design is to create a robust, precise and cost-effective system that improves the limitations of the present equipment on the market, such as robotic arms or rotary tables. For this reason, a preliminary study has been conducted to analyse the needs of improvement, later, we have focused on the 3D design and prototyping. For its construction, there have been used the FDM additive technology and structural components that are easy to find in the market. With regards to electronic components, basic electronics and Arduino-based 3D printers firmware have been selected. For system testing, the capture equipment consists of a Spider Artec 3D Scanner and a Nikon 5100 SLR Camera. Finally, 3D models have been developed by comparing the 3D meshes obtained by the two methods, obtaining satisfactory results.
The Influence of Users’ Spatial Familiarity on Their Emotional Perception of Space and Wayfinding Movement Patterns
Authors: Kim Ju Yeon , Choi Jin Kyung , Han Won Hee , Kim Jong Ha
Published: April 2021

In order to evaluate the sensory perceptions of users who visited a train station, this study aimed to conduct an evaluation of their spatial emotions and identify the distance and type of transfer. For evaluation and verification, emotional recognition and wayfinding types were analyzed according to types in the groups (gender, age, and spatial familiarity) of experimental participants. There were two research questions: “Will the length of movement patterns in the experiment environment vary depending on the types of the participant group?” and “Is there any moderating effect in the interaction between spatial familiarity and the types of the participant groups?” A total of 28 participants were recruited with consideration of gender, age, and familiarity with spatial experience, which were used to analyze the participant groups. The experiment was conducted at a train station, and a vignette was presented to the participants to record the route and pattern of their wayfinding, followed by providing a questionnaire to record their spatial perception. SPSS was used to conduct a T-test, factor analysis, and multidimensional scaling (MDS). The differences in spatial perception were arranged in visual positioning based on emotional vocabulary, and average movement distances in the participant groups were compared in accordance with the type of wayfinding and interaction effect by ANOVA. The results showed that there was a difference in spatial perception depending on the negative emotional vocabulary and type of participant. An emotional positioning map for average comparison was prepared for each participant group (gender, age, and spatial familiarity) by using the factors extracted in the factor analysis (emotional factor, management factor, and aesthetic factor). Female and unfamiliar groups displayed negative results in the emotional factor (F = 7.202, p < 0.05). In addition, male and familiar groups displayed negative results in the management factor (F = 3.058, p < 0.10). In wayfinding, there was an interaction between gender and the resident group based on the status of their spatial familiarity. Through this, it was possible to extract negative emotional evaluations according to the type of participant and the interaction factors for the type and length of the wayfinding.