bluuebunny/crossref_metadata_2025 huggingface dataset:
A Semi-Mechanistic Prediction of Residence Time Metrics in Twin Screw Granulation
Authors: Muddu Shashank Venkat , Kotamarthy Lalith , Ramachandran Rohit
Published: March 2021

This work is concerned with the semi-mechanistic prediction of residence time metrics using historical data from mono-component twin screw wet granulation processes. From the data, several key parameters such as powder throughput rate, shafts rotation speed, liquid binder feed ratio, number of kneading elements in the shafts and the stagger angle between the kneading elements were identified and physical factors were developed to translate those varying parameters into expressions affecting the key intermediate phenomena in the equipment, holdup, flow and mixing. The developed relations were then tested across datasets to evaluate the performance of the model, applying a k-fold optimization technique. The semi-mechanistic predictions were evaluated both qualitatively through the main effects plots and quantitatively through the parity plots and correlations between the tuning constants across datasets. The root mean square error (RMSE) was used as a metric to compare the degree of goodness of fit for different datasets using the developed semi-mechanistic relations. In summary this paper presents a new approach at estimating both the residence time metrics in twin screw wet granulation, mean residence time (MRT) and variance through semi-mechanistic relations, the validity of which have been tested for different datasets.
Genetically Encoded Self-Assembling Iron Oxide Nanoparticles as a Possible Platform for Cancer-Cell Tracking
Authors: Efremova Maria , Bodea Silviu-Vasile , Sigmund Felix , Semkina Alevtina , Westmeyer Gil , Abakumov Maxim
Published: March 2021

The study of growth and possible metastasis in animal models of tumors would benefit from reliable cell labels for noninvasive whole-organism imaging techniques such as magnetic resonance imaging. Genetically encoded cell-tracking reporters have the advantage that they are contrast-selective for viable cells with intact protein expression machinery. Besides, these reporters do not suffer from dilution during cell division. Encapsulins, which are bacterial protein nanocompartments, can serve as genetically controlled labels for multimodal detection of cells. Such nanocompartments can host various guest molecules inside their lumen. These include, for example, fluorescent proteins or enzymes with ferroxidase activity leading to biomineralization of iron oxide inside the encapsulin nanoshell. The aim of this work was to implement heterologous expression of encapsulin systems from Quasibacillus thermotolerans using the fluorescent reporter protein mScarlet-I and ferroxidase IMEF in the human hepatocellular carcinoma cell line HepG2. The successful expression of self-assembled encapsulin nanocompartments with functional cargo proteins was confirmed by fluorescence microscopy and transmission electron microscopy. Also, coexpression of encapsulin nanoshells, ferroxidase cargo, and iron transporter led to an increase in T2-weighted contrast in magnetic resonance imaging of HepG2 cells. The results demonstrate that the encapsulin cargo system from Q. thermotolerans may be suitable for multimodal imaging of cancer cells and could contribute to further in vitro and in vivo studies.
Drug–Drug Compatibility Evaluation of Sulfasalazine and Folic Acid for Fixed-Dose Combination Development Using Various Analytical Tools
Authors: Jeličić Mario-Livio , Brusač Edvin , Kurajica Stanislav , Cvetnić Matija , Amidžić Klarić Daniela , Nigović Biljana , Mornar Ana
Published: March 2021

The simultaneous administration of sulfasalazine and folic acid is regular practice in the therapy of inflammatory bowel diseases in order to maintain sufficient folate concentration in patients. Having multiple drugs in the therapy increases the possibility of patients failing adherence, thus unintentionally endangering their health. A fixed-dose combination of sulfasalazine and folic would simplify the classical polytherapeutic approach; however, the physicochemical compatibility investigation of two active pharmaceutical ingredients plays an important role in the development of such a product. In this work, various analytical tools were used to determine the physicochemical compatibility of sulfasalazine and folic acid. For the evaluation of chemical compatibility, infrared spectroscopy in combination with advanced statistical methods, such as the principal component analysis and cluster analysis, were used, whilst a simultaneous thermogravimetry/differential thermal analysis gave us an insight into the physical compatibility of two drugs. Isothermal stress testing, forced degradation and dissolution studies, followed by the analysis with a developed chromatographic method for the monitoring of folic acid, sulfasalazine and two of its related impurities, sulfapyridine and salicylic acid, gave us an insight into its chemical compatibility. The combination of the results obtained from the used techniques implies a satisfactory physicochemical compatibility between sulfasalazine and folic acid, which opens the path to the development of the proposed fixed-dose combination.
Production of Fuel from Plastic Waste: A Feasible Business
Authors: Fahim Irene , Mohsen Omar , ElKayaly Dina
Published: March 2021

This paper aims to conduct a feasibility study of producing fuel from plastic waste. It is a suggested approach to deal with the huge production of synthetic plastic around the world, so as to avoid its accumulation in landfills and the depletion of resources. Several types of research have addressed the conversion of plastic waste into energy, and in this study the authors focused on using pyrolysis to convert plastic to liquid oil. Accordingly, the volume of the waste was reduced significantly, and the produced liquid oil had a high calorific value in comparison to fossil fuel. The authors managed to develop a profitable business model for a facility producing fuel from plastic waste in Egypt. This project could be a very lucrative business opportunity for investors or venture capitalists interested in investing in green economy. A Business Model Canvas was used as a tool to identify how the different components of the business relate to each other.
Electrospun Nanofibrous Scaffolds: Review of Current Progress in the Properties and Manufacturing Process, and Possible Applications for COVID-19
Authors: Kchaou Mohamed , Alquraish Mohammed , Abuhasel Khaled , Abdullah Ahmad , Ali Ashraf A.
Published: March 2021

Over the last twenty years, researchers have focused on the potential applications of electrospinning, especially its scalability and versatility. Specifically, electrospun nanofiber scaffolds are considered an emergent technology and a promising approach that can be applied to biosensing, drug delivery, soft and hard tissue repair and regeneration, and wound healing. Several parameters control the functional scaffolds, such as fiber geometrical characteristics and alignment, architecture, etc. As it is based on nanotechnology, the concept of this approach has shown a strong evolution in terms of the forms of the materials used (aerogels, microspheres, etc.), the incorporated microorganisms used to treat diseases (cells, proteins, nuclei acids, etc.), and the manufacturing process in relation to the control of adhesion, proliferation, and differentiation of the mimetic nanofibers. However, several difficulties are still considered as huge challenges for scientists to overcome in relation to scaffolds design and properties (hydrophilicity, biodegradability, and biocompatibility) but also in relation to transferring biological nanofibers products into practical industrial use by way of a highly efficient bio-solution. In this article, the authors review current progress in the materials and processes used by the electrospinning technique to develop novel fibrous scaffolds with suitable design and that more closely mimic structure. A specific interest will be given to the use of this approach as an emergent technology for the treatment of bacteria and viruses such as COVID-19.
Comparative Studies on Crystallinity, Thermal and Mechanical Properties of Polyketone Grown on Plasma Treated CVD Graphene
Authors: Cho Sunghun , Lee Jun Seop , Jang Hyeji , Park Seorin , An Ji Hyun , Jang Jyongsik
Published: March 2021

In this work, we report a facile way to control crystalline structures of polyketone (PK) films by combining plasma surface treatment with chemical vapor deposition (CVD) technique. The crystalline structure of PKs grown on plasma-treated graphene and the resulting thermal and mechanical properties were systematically discussed. Every graphene sheet used in this work was produced by CVD method and the production of PKs having different crystallinity were performed on the O2- and N2-doped graphene sheets. It was evident that the CVD-grown graphene sheets acted as the nucleating agents for promoting the crystallization of β-form PK, while suppressing the growth of α-form PK crystals. Regardless of the increase in surface roughness of graphene, surface functionality of the CVD-grown graphene was found to be an important factor in determining the crystalline structure of PK. N2 plasma treatment of the CVD-grown graphene promoted growth of the β-form PK, whereas the O2 plasma treatment of CVD graphene led to transformation of the unoriented β-form PK into the oriented α-form PK. Thus, the resulting thermal and mechanical properties of the PKs were highly dependent on the surface functionality of the CVD graphene. The method of controlling crystalline structure of the PKs suggested in this study, is expected to be very effective in realizing the PK with good processability, heat resistance and mechanical properties.
Experimental Study of the Effect of High Service Temperature on the Flexural Performance of Near-Surface Mounted (NSM) Carbon Fiber-Reinforced Polymer (CFRP)-Strengthened Concrete Beams
Authors: Jahani Younes , Baena Marta , Gómez Javier , Barris Cristina , Torres Lluís
Published: March 2021

This paper presents a study of the effect of high service temperature (near or beyond glass transition temperature (Tg) of structural epoxy adhesive) on the behavior of near-surface mounted (NSM) carbon fiber-reinforced polymer (CFRP)-strengthened reinforced concrete (RC) beams. The study includes experimental work as well as analytical and numerical analysis. To this end, fourteen beams have been tested up to failure in two different series. In series 1, specimens with three different CFRP areas have been tested at two different temperatures (i.e., 20 and 40 °C). In series 2, and with the aim of evaluating the effect of higher temperatures, only one CFRP area was tested under four different temperatures (i.e., 20, 60, 70, and 85 °C). Experimental results are evaluated in terms of load–deflections, failure modes, and bond performance. Furthermore, the experimental load–deflection curves are satisfactorily compared to both analytical predictions and finite element (FE) numerical simulations. In both cases, shrinkage and temperature effects on the short-term response of flexural elements have been accounted for. No significant reduction in stiffness and ultimate load was observed for specimens being tested up to 60 °C (in the range of epoxy Tg), showing FRP rupture failure in all of them. For specimens under 70 and 85 °C, the failure mode changed from FRP rupture to FRP end debonding and concrete crushing, respectively.
Polylactide/Polyvinylalcohol-Based Porous Bioscaffold Loaded with Gentamicin for Wound Dressing Applications
Authors: Amini Moghaddam Maliheh , Di Martino Antonio , Šopík Tomáš , Fei Haojie , Císař Jaroslav , Pummerová Martina , Sedlařík Vladimír
Published: March 2021

This study explores the feasibility of modifying the surface liquid spraying method to prepare porous bioscaffolds intended for wound dressing applications. For this purpose, gentamicin sulfate was loaded into polylactide-polyvinyl alcohol bioscaffolds as a highly soluble (hygroscopic) model drug for in vitro release study. Moreover, the influence of inorganic salts including NaCl (10 g/L) and KMnO4 (0.4 mg/L), and post-thermal treatment (T) (80 °C for 2 min) on the properties of the bioscaffolds were studied. The bioscaffolds were characterized by scanning electron microscopy, Fourier Transform infrared spectroscopy, and differential scanning calorimetry. In addition, other properties including porosity, swelling degree, water vapor transmission rate, entrapment efficiency, and the release of gentamicin sulfate were investigated. Results showed that high concentrations of NaCl (10 g/L) in the aqueous phase led to an increase of around 68% in the initial burst release due to the increase in porosity. In fact, porosity increased from 68.1 ± 1.2 to 94.1 ± 1.5. Moreover, the thermal treatment of the Polylactide-polyvinyl alcohol/NaCl (PLA-PVA/NaCl) bioscaffolds above glass transition temperature (Tg) reduced the initial burst release by approximately 11% and prolonged the release of the drug. These results suggest that thermal treatment of polymer above Tg can be an efficient approach for a sustained release.
CeO2 Nanoparticle-Containing Polymers for Biomedical Applications: A Review
Authors: Shcherbakov Alexander B. , Reukov Vladimir V. , Yakimansky Alexander V. , Krasnopeeva Elena L. , Ivanova Olga S. , Popov Anton L. , Ivanov Vladimir K.
Published: March 2021

The development of advanced composite biomaterials combining the versatility and biodegradability of polymers and the unique characteristics of metal oxide nanoparticles unveils new horizons in emerging biomedical applications, including tissue regeneration, drug delivery and gene therapy, theranostics and medical imaging. Nanocrystalline cerium(IV) oxide, or nanoceria, stands out from a crowd of other metal oxides as being a truly unique material, showing great potential in biomedicine due to its low systemic toxicity and numerous beneficial effects on living systems. The combination of nanoceria with new generations of biomedical polymers, such as PolyHEMA (poly(2-hydroxyethyl methacrylate)-based hydrogels, electrospun nanofibrous polycaprolactone or natural-based chitosan or cellulose, helps to expand the prospective area of applications by facilitating their bioavailability and averting potential negative effects. This review describes recent advances in biomedical polymeric material practices, highlights up-to-the-minute cerium oxide nanoparticle applications, as well as polymer-nanoceria composites, and aims to address the question: how can nanoceria enhance the biomedical potential of modern polymeric materials?
Correction: Wei, Y.; et al. Quantify the Protein-Protein Interaction Effects on Adsorption Related Lubricating Behaviors of α-Amylase on a Glass Surface. Polymers 2020, 12, 1658
Authors: Baskaran Nareshkumar , Chang You-Cheng , Chang Chia-Hua , Hung Shun-Kai , Kao Chuan-Tse , Wei Yang
Published: March 2021

The authors wish to make the following corrections to this paper [...]
Superabsorbent Polymer Network Degradable by a Human Urinary Enzyme
Authors: Whang Minji , Yu Hyeonji , Kim Jungwook
Published: March 2021

Owing to its superior water absorption capacity, superabsorbent polymer (SAP) based on a poly (acrylic acid) network is extensively used in industrial products such as diapers, wound dressing, or surgical pads. However, because SAP does not degrade naturally, a massive amount of non-degradable waste is discarded daily, posing serious environmental problems. Considering that diapers are the most widely used end-product of SAP, we created one that is degradable by a human urinary enzyme. We chose three enzyme candidates, all of which have substrates that were modified with polymerizable groups to be examined for cleavable crosslinkers of SAP. We found that the urokinase-type plasminogen activator (uPA) substrate, end-modified with acrylamide groups at sufficient distances from the enzymatic cleavage site, can be successfully used as a cleavable crosslinker of SAP. The resulting SAP slowly degraded over several days in the aqueous solution containing uPA at a physiological concentration found in human urine and became shapeless in ~30 days.
An Evaluation of the Effects of UAS Flight Parameters on Digital Aerial Photogrammetry Processing and Dense-Cloud Production Quality in a Scots Pine Forest
Authors: de Lima Raul Sampaio , Lang Mait , Burnside Niall G. , Peciña Miguel Villoslada , Arumäe Tauri , Laarmann Diana , Ward Raymond D. , Vain Ants , Sepp Kalev
Published: March 2021

The application of unmanned aerial systems (UAS) in forest research includes a wide range of equipment, systems, and flight settings, creating a need for enhancing data acquisition efficiency and quality. Thus, we assessed the effects of flying altitude and lateral and longitudinal overlaps on digital aerial photogrammetry (DAP) processing and the ability of its products to provide point clouds for forestry inventory. For this, we used 18 combinations of flight settings for data acquisition, and a nationwide airborne laser scanning (ALS) dataset as reference data. Linear regression was applied for modeling DAP quality indicators and model fitting quality as the function of flight settings; equivalence tests compared DAP- and ALS-products. Most of DAP-Digital Terrain Models (DTM) showed a moderate to high agreement (R2 > 0.70) when fitted to ALS-based models; nine models had a regression slope within the 1% region of equivalence. The best DAP-Canopy Height Model (CHM) was generated using ALS-DTM with an R2 = 0.42 when compared with ALS-CHM, indicating reduced similarity. Altogether, our results suggest that the optimal combination of flight settings should include a 90% lateral overlap, a 70% longitudinal overlap, and a minimum altitude of 120 m above ground level, independent of the availability of an ALS-derived DTM for height normalization. We also provided insights into the effects of flight settings on DAP outputs for future applications in similar forest stands, emphasizing the benefits of overlaps for comprehensive scene reconstruction and altitude for canopy surface detection.
Fast and Accurate Terrain Image Classification for ASTER Remote Sensing by Data Stream Mining and Evolutionary-EAC Instance-Learning-Based Algorithm
Authors: Hu Shimin , Fong Simon , Yang Lili , Yang Shuang-Hua , Dey Nilanjan , Millham Richard C. , Fiaidhi Jinan
Published: March 2021

Remote sensing streams continuous data feed from the satellite to ground station for data analysis. Often the data analytics involves analyzing data in real-time, such as emergency control, surveillance of military operations or scenarios that change rapidly. Traditional data mining requires all the data to be available prior to inducing a model by supervised learning, for automatic image recognition or classification. Any new update on the data prompts the model to be built again by loading in all the previous and new data. Therefore, the training time will increase indefinitely making it unsuitable for real-time application in remote sensing. As a contribution to solving this problem, a new approach of data analytics for remote sensing for data stream mining is formulated and reported in this paper. Fresh data feed collected from afar is used to approximate an image recognition model without reloading the history, which helps eliminate the latency in building the model again and again. In the past, data stream mining has a drawback in approximating a classification model with a sufficiently high level of accuracy. This is due to the one-pass incremental learning mechanism inherently exists in the design of the data stream mining algorithm. In order to solve this problem, a novel streamlined sensor data processing method is proposed called evolutionary expand-and-contract instance-based learning algorithm (EEAC-IBL). The multivariate data stream is first expanded into many subspaces, and then the subspaces, which are corresponding to the characteristics of the features are selected and condensed into a significant feature subset. The selection operates stochastically instead of deterministically by evolutionary optimization, which approximates the best subgroup. Followed by data stream mining, the model learning for image recognition is done on the fly. This stochastic approximation method is fast and accurate, offering an alternative to the traditional machine learning method for image recognition application in remote sensing. Our experimental results show computing advantages over other classical approaches, with a mean accuracy improvement at 16.62%.
The openEO API–Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities
Authors: Schramm Matthias , Pebesma Edzer , Milenković Milutin , Foresta Luca , Dries Jeroen , Jacob Alexander , Wagner Wolfgang , Mohr Matthias , Neteler Markus , Kadunc Miha , Miksa Tomasz , Kempeneers Pieter , Verbesselt Jan , Gößwein Bernhard , Navacchi Claudio , Lippens Stefaan , Reiche Johannes
Published: March 2021

At present, accessing and processing Earth Observation (EO) data on different cloud platforms requires users to exercise distinct communication strategies as each backend platform is designed differently. The openEO API (Application Programming Interface) standardises EO-related contracts between local clients (R, Python, and JavaScript) and cloud service providers regarding data access and processing, simplifying their direct comparability. Independent of the providers’ data storage system, the API mimics the functionalities of a virtual EO raster data cube. This article introduces the communication strategy and aspects of the data cube model applied by the openEO API. Two test cases show the potential and current limitations of processing similar workflows on different cloud platforms and a comparison of the result of a locally running workflow and its openEO-dependent cloud equivalent. The outcomes demonstrate the flexibility of the openEO API in enabling complex scientific analysis of EO data collections on cloud platforms in a homogenised way.
Comparison of Hyperspectral Imaging and Near-Infrared Spectroscopy to Determine Nitrogen and Carbon Concentrations in Wheat
Authors: Tahmasbian Iman , Morgan Natalie K. , Hosseini Bai Shahla , Dunlop Mark W. , Moss Amy F.
Published: March 2021

Hyperspectral imaging (HSI) is an emerging rapid and non-destructive technology that has promising application within feed mills and processing plants in poultry and other intensive animal industries. HSI may be advantageous over near infrared spectroscopy (NIRS) as it scans entire samples, which enables compositional gradients and sample heterogenicity to be visualised and analysed. This study was a preliminary investigation to compare the performance of HSI with that of NIRS for quality measurements of ground samples of Australian wheat and to identify the most important spectral regions for predicting carbon (C) and nitrogen (N) concentrations. In total, 69 samples were scanned using an NIRS (400–2500 nm), and two HSI cameras operated in 400–1000 nm (VNIR) and 1000–2500 nm (SWIR) spectral regions. Partial least square regression (PLSR) models were used to correlate C and N concentrations of 63 calibration samples with their spectral reflectance, with 6 additional samples used for testing the models. The accuracy of the HSI predictions (full spectra) were similar or slightly higher than those of NIRS (NIRS Rc2 for C = 0.90 and N = 0.96 vs. HSI Rc2 for C (VNIR) = 0.97 and N (SWIR) = 0.97). The most important spectral region for C prediction identified using HSI reflectance was 400–550 nm with R2 of 0.93 and RMSE of 0.17% in the calibration set and R2 of 0.86, RMSE of 0.21% and ratio of performance to deviation (RPD) of 2.03 in the test set. The most important spectral regions for predicting N concentrations in the feed samples included 1451–1600 nm, 1901–2050 nm and 2051–2200 nm, providing prediction with R2 ranging from 0.91 to 0.93, RMSE ranging from 0.06% to 0.07% in the calibration sets, R2 from 0.96 to 0.99, RMSE of 0.06% and RPD from 3.47 to 3.92 in the test sets. The prediction accuracy of HSI and NIRS were comparable possibly due to the larger statistical population (larger number of pixels) that HSI provided, despite the fact that HSI had smaller spectral range compared with that of NIRS. In addition, HSI enabled visualising the variability of C and N in the samples. Therefore, HSI is advantageous compared to NIRS as it is a multifunctional tool that poses many potential applications in data collection and quality assurance within feed mills and poultry processing plants. The ability to more accurately measure and visualise the properties of feed ingredients has potential economic benefits and therefore additional investigation and development of HSI in this application is warranted.
Correction of Directional Effects in VEGETATION NDVI Time-Series
Authors: León-Tavares Jonathan , Roujean Jean-Louis , Smets Bruno , Wolters Erwin , Toté Carolien , Swinnen Else
Published: March 2021

Land surface reflectance measurements from the VEGETATION program (SPOT-4, SPOT-5 and PROBA-V satellites) have led to the acquisition of consistent time-series of Normalized Difference Vegetation Index (NDVI) at a global scale. The wide imaging swath (>2000 km) of the family of VEGETATION space-borne sensors ensures a daily coverage of the Earth at the expense of a varying observation and illumination geometries between successive orbit overpasses for a given target located on the ground. Such angular variations infer saw-like patterns on time-series of reflectance and NDVI. The presence of directional effects is not a real issue provided that they can be properly removed, which supposes an appropriate BRDF (Bidirectional Reflectance Distribution Function) sampling as offered by the VEGETATION program. An anisotropy correction supports a better analysis of the temporal shapes and spatial patterns of land surface reflectance values and vegetation indices such as NDVI. Herein we describe a BRDF correction methodology, for the purpose of the Copernicus Global Land Service framework, which includes notably an adaptive data accumulation window and provides uncertainties associated with the NDVI computed with normalized reflectance. Assessing the general performance of the methodology in comparing time-series between normalized and directional NDVI reveals a significant removal of the high-frequency noise due to directional effects. The proposed methodology is computationally efficient to operate at a global scale to deliver a BRDF-corrected NDVI product based on long-term Time-Series of VEGETATION sensor and its follow-on with the Copernicus Sentinel-3 satellite constellation.
Underground Coal Fire Detection and Monitoring Based on Landsat-8 and Sentinel-1 Data Sets in Miquan Fire Area, XinJiang
Authors: Liu Jinglong , Wang Yunjia , Yan Shiyong , Zhao Feng , Li Yi , Dang Libo , Liu Xixi , Shao Yaqin , Peng Bin
Published: March 2021

Underground coal fires have become a worldwide disaster, which brings serious environmental pollution and massive energy waste. Xinjiang is one of the regions that is seriously affected by the underground coal fires. After years of extinguishing, the underground coal fire areas in Xinjiang have not been significantly reduced yet. To extinguish underground coal fires, it is critical to identify and monitor them. Recently, remote sensing technologies have been showing great potential in coal fires’ identification and monitoring. The thermal infrared technology is usually used to detect thermal anomalies in coal fire areas, and the Differential Synthetic Aperture Radar Interferometry (DInSAR) technology for the detection of coal fires related to ground subsidence. However, non-coal fire thermal anomalies caused by ground objects with low specific heat capacity, and surface subsidence caused by mining and crustal activities have seriously affected the detection accuracy of coal fire areas. To improve coal fires’ detection accuracy by using remote sensing technologies, this study firstly obtains temperature, normalized difference vegetation index (NDVI), and subsidence information based on Landsat8 and Sentinel-1 data, respectively. Then, a multi-source information strength and weakness constraint method (SWCM) is proposed for coal fire identification and analysis. The results show that the proposed SWCM has the highest coal fire identification accuracy among the employed methods. Moreover, it can significantly reduce the commission and omission error caused by non-coal fire-related thermal anomalies and subsidence. Specifically, the commission error is reduced by 70.4% on average, and the omission error is reduced by 30.6%. Based on the results, the spatio-temporal change characteristics of the coal fire areas have been obtained. In addition, it is found that there is a significant negative correlation between the time-series temperature and the subsidence rate of the coal fire areas (R2 reaches 0.82), which indicates the feasibility of using both temperature and subsidence to identify and monitor underground coal fires.
Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping
Authors: Bhandari Mahendra , Baker Shannon , Rudd Jackie C. , Ibrahim Amir M. H. , Chang Anjin , Xue Qingwu , Jung Jinha , Landivar Juan , Auvermann Brent
Published: March 2021

Drought significantly limits wheat productivity across the temporal and spatial domains. Unmanned Aerial Systems (UAS) has become an indispensable tool to collect refined spatial and high temporal resolution imagery data. A 2-year field study was conducted in 2018 and 2019 to determine the temporal effects of drought on canopy growth of winter wheat. Weekly UAS data were collected using red, green, and blue (RGB) and multispectral (MS) sensors over a yield trial consisting of 22 winter wheat cultivars in both irrigated and dryland environments. Raw-images were processed to compute canopy features such as canopy cover (CC) and canopy height (CH), and vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Excess Green Index (ExG), and Normalized Difference Red-edge Index (NDRE). The drought was more severe in 2018 than in 2019 and the effects of growth differences across years and irrigation levels were visible in the UAS measurements. CC, CH, and VIs, measured during grain filling, were positively correlated with grain yield (r = 0.4–0.7, p < 0.05) in the dryland in both years. Yield was positively correlated with VIs in 2018 (r = 0.45–0.55, p < 0.05) in the irrigated environment, but the correlations were non-significant in 2019 (r = 0.1 to −0.4), except for CH. The study shows that high-throughput UAS data can be used to monitor the drought effects on wheat growth and productivity across the temporal and spatial domains.
Building Damage Detection Based on OPCE Matching Algorithm Using a Single Post-Event PolSAR Data
Authors: Nie Yuliang , Zeng Qiming , Zhang Haizhen , Wang Qing
Published: March 2021

Synthetic aperture radar (SAR) is an effective tool in detecting building damage. At present, more and more studies detect building damage using a single post-event fully polarimetric SAR (PolSAR) image, because it permits faster and more convenient damage detection work. However, the existence of non-buildings and obliquely-oriented buildings in disaster areas presents a challenge for obtaining accurate detection results using only post-event PolSAR data. To solve these problems, a new method is proposed in this work to detect completely collapsed buildings using a single post-event full polarization SAR image. The proposed method makes two improvements to building damage detection. First, it provides a more effective solution for non-building area removal in post-event PolSAR images. By selecting and combining three competitive polarization features, the proposed solution can remove most non-building areas effectively, including mountain vegetation and farmland areas, which are easily confused with collapsed buildings. Second, it significantly improves the classification performance of collapsed and standing buildings. A new polarization feature was created specifically for the classification of obliquely-oriented and collapsed buildings via development of the optimization of polarimetric contrast enhancement (OPCE) matching algorithm. Using this developed feature combined with texture features, the proposed method effectively distinguished collapsed and obliquely-oriented buildings, while simultaneously also identifying the affected collapsed buildings in error-prone areas. Experiments were implemented on three PolSAR datasets obtained in fully polarimetric mode: Radarsat-2 PolSAR data from the 2010 Yushu earthquake in China (resolution: 12 m, scale of the study area: 50 km2); ALOS PALSAR PolSAR data from the 2011 Tohoku tsunami in Japan (resolution: 23.14 m, scale of the study area: 113 km2); and ALOS-2 PolSAR data from the 2016 Kumamoto earthquake in Japan (resolution: 5.1 m, scale of the study area: 5 km2). Through the experiments, the proposed method was proven to obtain more than 90% accuracy for built-up area extraction in post-event PolSAR data. The achieved detection accuracies of building damage were 82.3%, 97.4%, and 78.5% in Yushu, Ishinomaki, and Mashiki town study sites, respectively.
Wearable Sensor Clothing for Body Movement Measurement during Physical Activities in Healthcare
Authors: Ancans Armands , Greitans Modris , Cacurs Ricards , Banga Beate , Rozentals Artis
Published: March 2021

This paper presents a wearable wireless system for measuring human body activities, consisting of small inertial sensor nodes and the main hub for data transmission via Bluetooth for further analysis. Unlike optical and ultrasonic technologies, the proposed solution has no movement restrictions, such as the requirement to stay in the line of sight, and it provides information on the dynamics of the human body’s poses regardless of its location. The problem of the correct placement of sensors on the body is considered, a simplified architecture of the wearable clothing is described, an experimental set-up is developed and tests are performed. The system has been tested by performing several physical exercises and comparing the performance with the commercially available BTS Bioengineering SMART DX motion capture system. The results show that our solution is more suitable for complex exercises as the system based on digital cameras tends to lose some markers. The proposed wearable sensor clothing can be used as a multi-purpose data acquisition device for application-specific data analysis, thus providing an automated tool for scientists and doctors to measure patient’s body movements.
Chiral Dielectric Metasurfaces for Highly Integrated, Broadband Circularly Polarized Antenna
Authors: Ferreira-Gomes Bruno , Oliveira Osvaldo N. , Mejía-Salazar Jorge Ricardo
Published: March 2021

We report on the design of a low-profile integrated millimeter-wave antenna for efficient and broadband circularly polarized electromagnetic radiation. The designed antenna comprises a chiral dielectric metasurface built with a 2×2 arrangement of dielectric cylinders with slanted-slots at the center. A broadbeam high-gain with wide axial ratio (AR)<3 dB bandwidth was reached by pairing the electric and magnetic resonances of the dielectric cylinders and the slanted slots when excited by an elliptically polarized driven-patch antenna. This electric-magnetic pairing can be tuned by varying the cylinders diameter and the tilting and rotation angles of the slanted slots. The simulation results indicate impedance-matching bandwidths up to 22.6% (25.3–31.6 GHz) with 3-dB AR bandwidths of 11.6% (26.9–30.2 GHz), which in terms of compactness (0.95λ0×0.95λ0) and performance are superior to previous antenna designs. Since the simulations were performed by assuming materials and geometries easily implementable experimentally, it is hoped that circularly polarized antennas based on chiral metasurfaces can be integrated into 5G and satellite communications.
Standards-Compliant Multi-Protocol On-Board Unit for the Evaluation of Connected and Automated Mobility Services in Multi-Vendor Environments
Authors: Sedar Roshan , Vázquez-Gallego Francisco , Casellas Ramon , Vilalta Ricard , Muñoz Raul , Silva Rodrigo , Dizambourg Laurent , Fernández Barciela Antonio Eduardo , Vilajosana Xavier , Datta Soumya Kanti , Härri Jérôme , Alonso-Zarate Jesus
Published: March 2021

Vehicle-to-everything (V2X) communications enable real-time information exchange between vehicles and infrastructure, which extends the perception range of vehicles beyond the limits of on-board sensors and, thus, facilitating the realisation of cooperative, connected, and automated mobility (CCAM) services that will improve road safety and traffic efficiency. In the context of CCAM, the successful deployments of cooperative intelligent transport system (C-ITS) use cases, with the integration of advanced wireless communication technologies, are effectively leading to make transport safer and more efficient. However, the evaluation of multi-vendor and multi-protocol based CCAM service architectures can become challenging and complex. Additionally, conducting on-demand field trials of such architectures with real vehicles involved is prohibitively expensive and time-consuming. In order to overcome these obstacles, in this paper, we present the development of a standards-compliant experimental vehicular on-board unit (OBU) that supports the integration of multiple V2X protocols from different vendors to communicate with heterogeneous cloud-based services that are offered by several original equipment manufacturers (OEMs). We experimentally demonstrate the functionalities of the OBU in a real-world deployment of a cooperative collision avoidance service infrastructure that is based on edge and cloud servers. In addition, we measure end-to-end application-level latencies of multi-protocol supported V2X information flows to show the effectiveness of interoperability in V2X communications between different vehicle OEMs.
Home Gardening and the Social Divide of Suburban Space: Methodological Proposal for the Spatial Analysis of a Social Practice in the Greater Paris Urban Area
Authors: Darly Ségolène , Feuillet Thierry , Laforêt Clémence
Published: March 2021

This paper explores home gardening geography in metropolitan outskirts, seen as a major asset and challenge of the alternative suburban city model. Studies that estimate the domestic production of backyard gardens are scarce, but they all confirm the persistence of an ancient and “ordinary” phenomenon still firmly rooted in the food landscape of the globalised North cities. To fill a gap in European alternative urban and food systems studies, we focus on the case of two subsectors of the extended suburban belt of greater Paris agglomeration. We designed and performed a spatial analysis protocol that differentiates vegetable garden types to test spatial relationships between environmental and intrinsic factors and assess clustering patterns. We had to overcome several methodological barriers by building an original vegetable gardens database and applying distinct qualitative and quantitative methods. Our results show spatial home gardening patterns differentiation at three intertwined levels: At the micro-level of domestic space (according to the size and share of vegetable plots); at the house block level (according to their socio-economic and built environment profile); and at the level of the housing estates or urban agglomeration (according to the geography of social specialisation).
From Evidence to Design Solution—On How to Handle Evidence in the Design Process of Sustainable, Accessible and Health-Promoting Landscapes
Authors: Gramkow Marie C. , Sidenius Ulrik , Zhang Gaochao , Stigsdotter Ulrika K.
Published: March 2021

The work of landscape architects can contribute to the United Nation’s Sustainable Development Goals and the associated ‘Leave no one behind’ agenda by creating accessible and health-promoting green spaces (especially goals 3, 10 and 11). To ensure that the design of green space delivers accessibility and intended health outcomes, an evidence-based design process is recommended. This is a challenge, since many landscape architects are not trained in evidence-based design, and leading scholars have called for methods that can help landscape architects work in an evidence-based manner. This paper examines the implementation of a process model for evidence-based health design in landscape architecture. The model comprises four steps: ‘evidence collection’, ‘programming’, ‘designing’, and ‘evaluation’. The paper aims to demonstrate how the programming step can be implemented in the design of a health-promoting nature trail that is to offer people with mobility disabilities improved mental, physical and social health. We demonstrate how the programming step systematizes evidence into design criteria (evidence-based goals) and design solutions (how the design criteria are to be solved in the design). The results of the study are presented as a design ‘Program’, which we hope can serve as an example for landscape architects of how evidence can be translated into design.
Green Energies, Employment, and Institutional Quality: Some Evidence for the OECD
Authors: Aldieri Luigi , Barra Cristian , Ruggiero Nazzareno , Vinci Concetto Paolo
Published: March 2021

Using a sample of 19 OECD countries over the 1985–2011 period, we propose the application of fixed effects regression to appraise the impact of green energies on employment and to assess how the quality of institutions shapes the relationship. The evidence reported in this paper indicates that higher supply of green energies enhances employment, though the effect is crucially mediated by the quality of institutions, depending on the measure of institutional quality employed. Further, the relationship remains stable under both Kyoto agreements and the 2007 financial crisis.
Sustainable Palm Oil Certification Scheme Frameworks and Impacts: A Systematic Literature Review
Authors: Abdul Majid Norhana , Ramli Zaimah , Md Sum Sarmila , Awang Abd Hair
Published: March 2021

Sustainability certification schemes were introduced to the palm oil industry as a response to address the negative environmental and social impacts associated with the development of this industry. The first certification scheme for palm oil, the Roundtable of Sustainable Palm Oil (RSPO), was established in 2004, followed by other non-governmental initiatives to ensure the sustainable production of palm oil. Indonesia and Malaysia, the two largest palm oil producers in the world, established Indonesia Sustainable Palm Oil (ISPO) and Malaysia Sustainable Palm Oil (MSPO) in 2011 and 2015, respectively. This article aims to analyze the existing literature related to studies on the RSPO, MSPO and ISPO on the basis of articles identified from the SCOPUS (scopus.com) and Web of Science (clavirate.com) databases. Results showed that research on the RSPO has been widely conducted compared with that on MSPO and ISPO. Thus, further research on MSPO and ISPO is needed to understand the dynamics of the implementation of sustainability certification. This article also provides an insight on how sustainable certification in the palm oil industry, particularly MSPO, could contribute to achieving the Sustainable Development Goals (SDGs).
Sustainable Societal Peace through the Integration of Bioethics Principles and Value-Based Education
Authors: Moorthy Ravichandran , Selvadurai Sivapalan , Gill Sarjit S. , Gurunathan Angelina
Published: March 2021

We live in a world where hatred and conflicts divide individuals, society, and countries. Although all faith systems and school curriculums emphasize some degree of peaceful co-existence, love, and compassion, the real-world situation is indeed abysmal. How can a naturalistic and altruistic logic of bioethics enhance divine and human-centric values in enabling social cohesion? As such, this paper proposes the integration of bioethics and value-based education principles into the education curriculum to help mitigate social conflicts and promote harmony in society. By employing conceptual and theoretical reviews, the paper attempts to shed light on how these principles can help to mitigate hatred and conflicts in society. Further, through matrix analysis, the study shows the relationships between the four main bioethics principles, respect for autonomy, non-maleficence, beneficence, and justice, and the values expounded in value-based education. The study finds that by integrating bioethics principles into value-based education, learners are able to internalize the values of social cohesion and tolerance, and reflect these values in their learning experiences. Bioethics principles amplify the expressions of values promoted in value-based education, and this, in turn, motivates the learners to change from social conflict behaviors to social cohesion aptitude while dealing with others in society. Social cohesion enables individuals and groups to develop social bonds and societal peace ownership.
Comparative Study on Spatial Digital Mapping Methods of Soil Nutrients Based on Different Geospatial Technologies
Authors: Gao Li , Huang Mingjing , Zhang Wuping , Qiao Lei , Wang Guofang , Zhang Xumeng
Published: March 2021

Soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK) are important indicators of soil fertility when undertaking a quality evaluation. Obtaining a high-precision spatial distribution map of soil nutrients is of great significance for the differentiated management of nutrient resources and reducing non-point source pollution. However, the spatial heterogeneity of soil nutrients lead to uncertainty in the modeling process. To determine the best interpolation method, terrain, climate, and vegetation factors were used as auxiliary variables to participate in the investigation of soil nutrient spatial modeling in the present study. We used the mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and accuracy (Acc) of a dataset to comprehensively compare the performance of four different geospatial techniques: ordinary kriging (OK), regression kriging (RK), geographically weighted regression kriging (GWRK), and multiscale geographically weighted regression kriging (MGWRK). The results showed that the hybrid methods (RK, GWRK, and MGWRK) could improve the prediction accuracy to a certain extent when the residuals were spatially correlated; however, this improvement was not significant. The new MGWRK model has certain advantages in reducing the overall residual level, but it failed to achieve the desired accuracy. Considering the cost of modeling, the OK method still provides an interpolation method with a relatively simple analysis process and relatively reliable results. Therefore, it may be more beneficial to design soil sampling rationally and obtain higher-quality auxiliary variable data than to seek complex statistical methods to improve spatial prediction accuracy. This research provides a reference for the spatial mapping of soil nutrients at the farmland scale.