bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolution of Target-Site Resistance to Glyphosate in an Amaranthus palmeri Population from Argentina and Its Expression at Different Plant Growth Temperatures
Authors: Kaundun Shiv Shankhar , Jackson Lucy Victoria , Hutchings Sarah-Jane , Galloway Jonathan , Marchegiani Elisabetta , Howell Anushka , Carlin Ryan , Mcindoe Eddie , Tuesca Daniel , Moreno Raul
Published: November 2019

The mechanism and expression of resistance to glyphosate at different plant growing temperatures was investigated in an Amaranthus palmeri population (VM1) from a soybean field in Vicuña Mackenna, Cordoba, Argentina. Resistance was not due to reduced glyphosate translocation to the meristem or to EPSPS duplication, as reported for most US samples. In contrast, a proline 106 to serine target-site mutation acting additively with EPSPS over-expression (1.8-fold increase) was respectively a major and minor contributor to glyphosate resistance in VM1. Resistance indices based on LD50 values generated using progenies from a cross between 52 PS106 VM1 individuals were estimated at 7.1 for homozygous SS106 and 4.3 for heterozygous PS106 compared with homozygous wild PP106 plants grown at a medium temperature of 24 °C day/18 °C night. A larger proportion of wild and mutant progenies survived a single commonly employed glyphosate rate when maintained at 30 °C day/26 °C night compared with 20 °C day/16 night in a subsequent experiment. Interestingly, the P106S mutation was not identified in any of the 920 plants analysed from 115 US populations, thereby potentially reflecting the difference in A. palmeri control practices in Argentina and USA.
Characterization of Cover Crop Rooting Types from Integration of Rhizobox Imaging and Root Atlas Information
Authors: Bodner Gernot , Loiskandl Willibald , Hartl Wilfried , Erhart Eva , Sobotik Monika
Published: November 2019

Plant root systems are essential for sustainable agriculture, conveying resource-efficient genotypes and species with benefits to soil ecosystem functions. Targeted selection of species/genotypes depends on available root system information. Currently there is no standardized approach for comprehensive root system characterization, suggesting the need for data integration across methods and sources. Here, we combine field measured root descriptors from the classical Root Atlas series with traits from controlled-environment root imaging for 10 cover crop species to (i) detect descriptors scaling between distant experimental methods, (ii) provide traits for species classification, and (iii) discuss implications for cover crop ecosystem functions. Results revealed relation of single axes measures from root imaging (convex hull, primary-lateral length ratio) to Root Atlas field descriptors (depth, branching order). Using composite root variables (principal components) for branching, morphology, and assimilate investment traits, cover crops were classified into species with (i) topsoil-allocated large diameter rooting type, (ii) low-branched primary/shoot-born axes-dominated rooting type, and (iii) highly branched dense rooting type, with classification trait-dependent distinction according to depth distribution. Data integration facilitated identification of root classification variables to derive root-related cover crop distinction, indicating their agro-ecological functions.
The Effects of Endogenous Hormones on the Flowering and Fruiting of Glycyrrhiza uralensis
Authors: Yan Binbin , Hou Junling , Cui Jie , He Chao , Li Wenbin , Chen Xiaoyu , Li Min , Wang Wenquan
Published: November 2019

Although endogenous hormones play an important role in flower bud differentiation and seed-filling, their effects on the flowering and fruiting of Glycyrrhiza uralensis Fisch. remain unknown. In the present study, we investigate the differences in the levels of endogenous hormones gibberellic acid (GA), abscisic acid (ABA), zeatin riboside (ZR), and indoleacetic acid (IAA) between the fruiting and seedless plants of G. uralensis Fisch. at different growth stages. We also determine the correlations of the endogenous hormone with the rates of flower and fruit falling, rate of empty seeds, rate of shrunken grains, and thousand kernel weight (TKW). The results demonstrate that the IAA and ZR levels of the flowering plants are significantly higher than those of the nonflowering plants at the flower bud differentiation stage. The GA and ABA levels of exfoliated inflorescence plants are considerably higher than those of the flowering and fruiting plants; the rates of falling flowers and fruit are negatively correlated with the IAA level and positively correlated with the ABA level. The ABA content of nonflowering plants is significantly higher than that of fruiting plants. The ZR:GA and IAA:ABA ratios are significantly positively correlated with TKW. The IAA:GA and IAA:ABA ratios are significantly negatively correlated with the rates of empty and shrunken seeds. Thus, we speculate that high IAA and ZR contents are good for flower bud differentiation and seed-filling, and low ABA and ZR contents are beneficial to flower bud development and seed-filling.
The Production Possibility of the Antimicrobial Filaments by Co-Extrusion of the PLA Pellet with Chitosan Powder for FDM 3D Printing Technology
Authors: Mania Szymon , Ryl Jacek , Jinn Jia-Rong , Wang Ya-Jane , Michałowska Anna , Tylingo Robert
Published: November 2019

The last decades have witnessed a major advancement and development in three-dimensional (3D) printing technology. In the future, the trend’s utilization of 3D printing is expected to play an important role in the biomedical field. This work presents co-extrusion of the polylactic acid (PLA), its derivatives (sPLA), and chitosan with the aim of achieving filaments for printing 3D objects, such as biomedical tools or implants. The physicochemical and antimicrobial properties were evaluated using SEM, FT-IR, DSC, instrumental mechanical test, and based on the ASTM E2149 standard, respectively. The addition of chitosan in the PLA and sPLA filaments increased their porosity and decreased density. The FT-IR analysis showed that PLA and chitosan only formed a physical mixture after extrusion. The addition of chitosan caused deterioration of the mechanical properties of filaments, especially elongation at break and Young’s modulus. The addition of chitosan to the filaments improved their ability to crystallize and provide their antimicrobial properties against Escherichia coli and Staphylococcus aureus.
Poly(Acrylonitrile–Butadiene–Styrene) as a Special β-Nucleating Agent on the Toughness of Isotactic Polypropylene
Authors: Liu Jingru , Zhu Xinxu , Cao Zheng
Published: November 2019

The influence of poly(acrylonitrile–butadiene–styrene) (ABS) as a special β-nucleating agent on the impact and tensile properties of isotactic polypropylene (iPP) were investigated by dynamic rheological measurements, wide-angle X-ray diffraction (WAXD), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and mechanical properties tests. It is found that the β nucleation efficiency of ABS is closely related to its concentration, dispersibility, and molding method for the iPP/ABS blends. The content of β-crystal (Kβ) rises with the incorporation of ABS and shows a maximum with the introduction of 1% ABS for compression-molded blends and 2% ABS for injection-molded blends, respectively, which is followed by a decrease in Kβ. The addition of a small amount of ABS has a significant reinforcing and toughening effect on iPP. Compared with the compression-molded samples, the ABS dispersed phase in injection-molded samples has a smaller particle size and a larger specific surface area, which are favorable for stress transmission and higher β nucleation efficiency, and therefore, better tensile and impact properties can be expected.
Design, Preparation, and Evaluation of a Novel Elastomer with Bio-Based Diethyl Itaconate Aiming at High-Temperature Oil Resistance
Authors: Yang Hui , Ji Haijun , Zhou Xinxin , Lei Weiwei , Zhang Liqun , Wang Runguo
Published: November 2019

A novel elastomer poly(diethyl itaconate-co-butyl acrylate-co-ethyl acrylate-co-glycidyl methacrylate) (PDEBEG) was designed and synthesized by redox emulsion polymerization based on bio-based diethyl itaconate, butyl acrylate, ethyl acrylate, and glycidyl methacrylate. The PDEBEG has a number average molecular weight of more than 200,000 and the yield is up to 96%. It is easy to control the glass transition temperature of the PDEBEG, which is ranged from −25.2 to −0.8 °C, by adjusting the monomer ratio. We prepared PDEBEG/CB composites by mixing PDEBEG with carbon black N330 and studied the oil resistance of the composites. The results show that the tensile strength and the elongation at break of the composites with 10 wt% diethyl itaconate can reach up to 14.5 MPa and 305%, respectively. The mechanical properties and high-temperature oil resistance of the composites are superior to that of the commercially available acrylate rubber AR72LS.
Gelatin Type A from Porcine Skin Used as Co-Initiator in a Radical Photo-Initiating System
Authors: Cosola Andrea , Chiappone Annalisa , Martinengo Cinzia , Grützmacher Hansjörg , Sangermano Marco
Published: November 2019

In the present study, a different approach for the preparation of poly(ethylene glycol) diacrylate-gelatin (PEGDA-gelatin) hydrogels was investigated. Gelatin type A from porcine skin was used as the co-initiator of a radical photo-initiating system instead of the traditional aliphatic or aromatic amines. This became possible because, upon visible-light irradiation, the amine sequences within gelatin generate initiating free-radicals through the intermolecular proton transfer in a Norrish type II reaction with camphorquinone (CQ). PEGDA-gelatin hydrogels were prepared by visible-light-induced photopolymerization. The gelatin content in the precursor formulations was varied. The influence of gelatin on the kinetics of the photocuring reaction was investigated, and it was found that gelatin fastened the rate of polymerization at all concentrations. The covalent attachment of gelatin segments within the cross-linked hydrogels was evaluated by means of attenuated total reflectance-infrared spectroscopy (ATR-FTIR) spectroscopy after solvent extraction. The thermo-mechanical properties, as well as the swelling behavior and gel content, were also investigated.
Advances in the Phototriggered Synthesis of Single-Chain Polymer Nanoparticles
Authors: Verde-Sesto Ester , Blázquez-Martín Agustín , Pomposo José A.
Published: November 2019

Clean use of photons from light to activate chemical reactions offers many possibilities in different fields, from chemistry and biology to materials science and medicine. This review article describes the advances carried out in last decades toward the phototriggered synthesis of single-chain polymer nanoparticles (SCNPs) as soft nanomaterials with promising applications in enzyme-mimicking catalysis and nanomedicine, among other different uses. First, we summarize some different strategies developed to synthesize SCNPs based on photoactivated intrachain homocoupling, phototriggered intrachain heterocoupling and photogenerated collapse induced by an external cross-linker. Next, we comprehensively review the emergent topic of photoactivated multifolding applied to SCNP construction. Finally, we conclude by summarizing recent strategies towards phototriggered disassembly of SCNPs.
French Salafists’ Economic Ethics: Between Election and New Forms of Politicization
Authors: Adraoui Mohamed-Ali
Published: November 2019

This article sheds light on the way in which activities such as the production and consumption of wealth are conceptualized, interpreted and put into practice within quietist Salafist communities in France. Unlike their jihadi and politicized counterparts, quietist Salafis in lands where Islam is the minority religion are required to emigrate to where Islam is majoritarian. As this article highlights, however, migrating is not necessarily a physical process. What is interesting to underline is that most French Salafists do not perform the Hijra, and favor, for instance, economic strategies allowing them to break with the rest of French society and live in ‘isolation’ rather than leaving France for good. Although framed as a religious duty, physical migration has been rare among French Salafist communities, whereas other forms of social rupture are emerging. The article explores in detail such economic strategies on the basis of the acceptance of neo-liberal principles allowing for what one can call an internal process of migration/isolation from French society.
The Anuvrat Movement: A Case Study of Jain-inspired Ethical and Eco-conscious Living
Authors: Reading Michael
Published: November 2019

From proclaiming the equality of all life forms to the stringent emphasis placed upon nonviolent behavior (ahimsa), and once more to the pronounced intention for limiting one’s possessions (aparigraha), Jainism has often been pointed to for its admirably ecofriendly example. Incorporating some of this eco-friendliness into its design for ethical vow taking, the Jain-inspired Anuvrat Movement, founded in 1949 by Acharya Sri Tulsi, today offers some arguably vital relevance for the urgent modern task to live eco-consciously. While such relevance includes, most explicitly, Anuvrat’s final vow (vow eleven) which calls for practitioners to “refrain from such acts as are likely to cause pollution and harm the environment,” and to avoid the “cutting down of trees” and the “wasting of water,”1 it also includes several of Anuvrat’s other vows as well, which carry significance on a more implicit level. Hence, presenting some of the basic history and philosophy behind Anuvrat, this article also analyzes its potential for ensuring ethical (and eco-conscious) behavior via its hallmark mechanism of vow restriction—a modality of arguably potent strategic and motivational value. Altogether, while first providing a brief inventory of Jain ecological practice in general, the article will then turn its attention to Anuvrat, arguing that when it comes to the modern eco-conscious imperative to “live simply so that others may simply live” (as the popular adage has it), there is indeed much that Anuvrat has to offer.
New Results from Strapdown Airborne Gravimetry Using Temperature Stabilisation
Authors: Jensen Tim E. , Olesen Arne V. , Forsberg Rene , Olsson Per-Anders , Josefsson Örjan
Published: November 2019

In recent years, the use of a strapdown Inertial Measurement Unit (IMU) for airborne gravimetry has proven itself to be an accurate and resilient measurement system, improving the operational flexibility. The main concern is erroneous long-wavelength information in the resulting estimates, which is suspected to originate from uncompensated long-term drift of the accelerometers, probably originating from temperature variation. For this reason, iMAR navigation has designed a temperature stabilisation box, which allows for temperature stabilisation of their IMU systems. On a regional airborne gravity survey over the Kattegat Sea between Denmark and Sweden, such a temperature stabilised strapdown IMU was operated alongside a traditional spring-type platform-stabilised gravity system from ZLS. An analysis of the difference in gravity estimates at cross-over locations yielded a mean value of −0.3 mGal for the iMAR system with an indicated accuracy of 1.0 mGal. The temperature stabilisation unit therefore effectively limits the accelerometer drift and improves the long-wavelength information. However, a straightforward merging approach, adjusting the line-based mean values of the iMAR estimates to match that of the ZLS estimates, improved the accuracy to 0.8 mGal. This indicates that the long-wavelength information of the stabilised-platform system is still superior to that of the strapdown system.
Urban-Rural Surface Temperature Deviation and Intra-Urban Variations Contained by an Urban Growth Boundary
Authors: Moffett Kevan B. , Makido Yasuyo , Shandas Vivek
Published: November 2019

The urban heat island (UHI) concept describes heat trapping that elevates urban temperatures relative to rural temperatures, at least in temperate/humid regions. In drylands, urban irrigation can instead produce an urban cool island (UCI) effect. However, the UHI/UCI characterization suffers from uncertainty in choosing representative urban/rural endmembers, an artificial dichotomy between UHIs and UCIs, and lack of consistent terminology for other patterns of thermal variation at nested scales. We use the case of a historically well-enforced urban growth boundary (UGB) around Portland (Oregon, USA): to explore the representativeness of the surface temperature UHI (SUHI) as derived from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data, to test common assumptions of characteristically “warm” or “cool” land covers (LCs), and to name other common urban thermal features of interest. We find that the UGB contains heat as well as sprawl, inducing a sharp surface temperature contrast across the urban/rural boundary. The contrast ranges widely depending on the end-members chosen, across a spectrum from positive (SUHI) to negative (SUCI) values. We propose a new, inclusive “urban thermal deviation” (UTD) term to span the spectrum of possible UHI-zero-UCI conditions. We also distinguish at finer scales “microthermal extremes” (MTEs), discrete areas tending in the same thermal direction as their LC or surroundings but to extreme (hot or cold) values, and microthermal anomalies (MTAs), that run counter to thermal expectations or tendencies for their LC or surroundings. The distinction is important because MTEs suggest a need for moderation in the local thermal landscape, whereas MTAs may suggest solutions.
Daily River Discharge Estimation Using Multi-Mission Radar Altimetry Data and Ensemble Learning Regression in the Lower Mekong River Basin
Authors: Kim Donghwan , Lee Hyongki , Chang Chi-Hung , Bui Duong Du , Jayasinghe Susantha , Basnayake Senaka , Chishtie Farrukh , Hwang Euiho
Published: November 2019

Estimating river discharge (Q) is critical for ecosystems and water resource management. Traditionally, estimating Q has depended on a single rating curve or the Manning equation. In contrast to the single rating curve, several rating curves at different locations have been linearly combined in an ensemble learning regression method to estimate Q (ELQ) at the Brazzaville gauge station in the central Congo River in a previous study. In this study, we further tested the proposed ELQ and apply it to the Lower Mekong River Basin (LMRB) with three locations: Stung Treng, Kratie, and Tan Chau. Two major advancements for estimating Q with ELQ are presented. First, ELQ successfully estimated Q at Tan Chau, downstream of Kratie, where hydrodynamic complexities exist. Since the hydrologic characteristics downstream of Kratie are extremely diverse and complex in time and space, most previous studies have estimated Q only upstream from Kratie with hydrologic models and statistical methods. Second, we estimated Q over the LMRB using ELQ with water levels (H) obtained from two radar altimetry missions, Envisat and Jason-2, which made it possible to estimate Q seamlessly from 2003 to 2016. Owing to ELQ with multi-mission radar altimetry data, we have overcome the problems of a single rating curve: Locations for estimating Q have to be close to virtual stations, e.g., a few tens of kilometers, because the performance of the single rating curve degrades as the distance between the location of Q estimation and a virtual station increases. Therefore, most previous studies had not used Jason-2 data whose cross-track interval is about 315 km at the equator. On the contrary, several H obtained from Jason-2 altimetry were used in this study regardless of distances from in-situ Q stations since the ELQ method compensates for degradation in the performance for Q estimation due to the poor rating curve with virtual stations away from in-situ Q stations. In general, the ELQ-estimated Q ( Q ^ E L Q ) showed more accurate results compared to those obtained from a single rating curve. In the case of Tan Chau, the root mean square error (RMSE) of Q ^ E L Q decreased by 1504/1338 m3/s using Envisat-derived H for the training/validation datasets. We successfully applied ELQ to the LMRB, which is one of the most complex basins to estimate Q with multi-mission radar altimetry data. Furthermore, our method can be used to obtain finer temporal resolution and enhance the performance of Q estimation with the current altimetry missions, such as Sentinel-3A/B and Jason-3.
Comparison and Validation of the Ionospheric Climatological Morphology of FY3C/GNOS with COSMIC during the Recent Low Solar Activity Period
Authors: Bai Weihua , Tan Guangyuan , Sun Yueqiang , Xia Junming , Cheng Cheng , Du Qifei , Wang Xianyi , Yang Guanglin , Liao Mi , Liu Yan , Meng Xiangguang , Zhao Danyang , Liu Congliang , Cai Yuerong , Wang Dongwei , Wang Yingqiang , Yin Cong , Hu Peng , Liu Ziyan
Published: November 2019

With the accumulation of the ionospheric radio occultation (IRO) data observed by Global Navigation Satellite System (GNSS) occultation sounder (GNOS) onboard FengYun-3C (FY3C) satellite, it is possible to use GNOS IRO data for ionospheric climatology research. Therefore, this work aims to validate the feasibility of FY3C/GNOS IRO products in climatology research by comparison with that of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), laying the foundation for its application in climatology study. Since previous verification works of FY3C/GNOS were done by comparison with ionosondes, this work matched NmF2/hmF2 of FY3C/GNOS and COSMIC into data pairs to verify the profile-level accuracy of FY3C/GNOS IRO data. The statistical results show that the overall correlation coefficients of both NmF2 and hmF2 are above 0.9, the overall bias and std of NmF2 differences between FY3C/GNOS and COSMIC are −2.19% and 17.48%, respectively, and the bias and std of hmF2 differences are −3.29 and 18.01 km, respectively, indicating a high profile-level precision consistency between FY3C/GNOS and COSMIC. In ionospheric climatology comparison, we divided NmF2/hmF2 of FY3C/GNOS into four seasons, then presented the season median NmF2/hmF2 in 5° × 10° grids and compared them with that of COSMIC. The results show that the ionospheric climatological characteristics of FY3C/GNOS and COSMIC are highly matched, both showing the typical climatological features such as equatorial ionosphere anomaly (EIA), winter anomaly, semiannual anomaly, Weddell Sea anomaly (WSA) and so on, though minor discrepancies do exist like the differences in magnitude of longitude peak structures and WSA, which verifies the reliability of FY3C/GNOS IRO products in ionospheric climatology research.
High-Resolution Sea Surface Temperature Retrieval from Landsat 8 OLI/TIRS Data at Coastal Regions
Authors: Jang Jae-Cheol , Park Kyung-Ae
Published: November 2019

High-resolution sea surface temperature (SST) images are essential to study the highly variable small-scale oceanic phenomena in a coastal region. Most previous SST algorithms are focused on the low or medium resolution SST from the near polar orbiting or geostationary satellites. The Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) makes it possible to obtain high-resolution SST images of coastal regions. This study performed a matchup procedure between 276 Landsat 8 images and in-situ temperature measurements of buoys off the coast of the Korean Peninsula from April 2013 to August 2017. Using the matchup database, we investigated SST errors for each formulation of the Multi-Channel SST (MCSST) and the Non-Linear SST (NLSST) by considering the satellite zenith angle (SZA) and the first-guess SST. The retrieved SST equations showed a root-mean-square error (RMSE) from 0.59 to 0.72 °C. The smallest errors were found for the NLSST equation that considers the SZA and uses the first-guess SST, compared with the MCSST equations. The SST errors showed characteristic dependences on the atmospheric water vapor, the SZA, and the wind speed. In spite of the narrow swath width of the Landsat 8, the effect of the SZA on the errors was estimated to be significant and considerable for all the formations. Although the coefficients were calculated in the coastal regions around the Korean Peninsula, these coefficients are expected to be feasible for SST retrieval applied to any other parts of the global ocean. This study also addressed the need for high-resolution coastal SST, by emphasizing the usefulness of the high-resolution Landsat 8 OLI/TIRS data for monitoring the small-scale oceanic phenomena in coastal regions.
Adaptive Least-Squares Collocation Algorithm Considering Distance Scale Factor for GPS Crustal Velocity Field Fitting and Estimation
Authors: Qu Wei , Chen Hailu , Liang Shichuan , Zhang Qin , Zhao Lihua , Gao Yuan , Zhu Wu
Published: November 2019

High-precision, high-reliability, and high-density GPS crustal velocity are extremely important requirements for geodynamic analysis. The least-squares collocation algorithm (LSC) has unique advantages over crustal movement models to overcome observation errors in GPS data and the sparseness and poor geometric distribution in GPS observations. However, traditional LSC algorithms often encounter negative covariance statistics, and thus, calculating statistical Gaussian covariance function based on the selected distance interval leads to inaccurate estimation of the correlation between the random signals. An unreliable Gaussian statistical covariance function also leads to inconsistency in observation noise and signal variance. In this study, we present an improved LSC algorithm that takes into account the combination of distance scale factor and adaptive adjustment to overcome these problems. The rationality and practicability of the new algorithm was verified by using GPS observations. Results show that the new algorithm introduces the distance scale factor, which effectively weakens the influence of systematic errors by improving the function model. The new algorithm can better reflect the characteristics of GPS crustal movement, which can provide valuable basic data for use in the analysis of regional tectonic dynamics using GPS observations.
Modeling and Assessment of GPS/Galileo/BDS Precise Point Positioning with Ambiguity Resolution
Authors: Liu Xuexi , Chen Hua , Jiang Weiping , Xi Ruijie , Zhao Wen , Song Chuanfeng , Zhou Xingyu
Published: November 2019

Multi-frequency and multi-GNSS integration is currently becoming an important trend in the development of satellite navigation and positioning technology. In this paper, GPS/Galileo/BeiDou (BDS) precise point positioning (PPP) with ambiguity resolution (AR) are discussed in detail. The mathematical model of triple-system PPP AR and the principle of fractional cycle bias (FCB) estimation are firstly described. With the data of 160 stations in Multi-GNSS Experiment (MGEX) from day of year (DOY) 321-350, 2018, the FCBs of the three systems are estimated and the experimental results show that the range of most GPS wide-lane (WL) FCB is within 0.1 cycles during one month, while that of Galileo WL FCB is 0.05 cycles. For BDS FCB, the classification estimation method is used to estimate the BDS FCB and divide it into GEO and non-GEO (IGSO and MEO) FCB. The variation range of BDS GEO WL FCB can reach 0.5 cycles, while BDS non-GEO WL FCB does not exceed 0.1 cycles within a month. However, the accuracies of GPS, Galileo, and BDS non-GEO narrow-lane (NL) FCB are basically the same. In addition, the number of visible satellites and Position Dilution of Precision (PDOP) values of different combined systems are analyzed and evaluated in this paper. It shows that the triple-system combination can significantly increase the number of observable satellites, optimize the spatial distribution structure of satellites, and is significantly superior to the dual-system and single-system. Finally, the positioning characteristics of single-, dual-, and triple-systems are analyzed. The results of the single station positioning experiment show that the accuracy and convergence speed of the fixed solutions for each system are better than those of the corresponding float solutions. The average root mean squares (RMSs) of the float and the fixed solution in the east and north direction for GPS/Galileo/BDS combined system are the smallest, being 0.92 cm, 0.52 cm and 0.50 cm, 0.46 cm respectively, while the accuracy of the GPS in the up direction is the highest, which is 1.44 cm and 1.27 cm, respectively. Therefore, the combined system can accelerate the convergence speed and greatly enhance the stability of the positioning results.
Enhanced Feature Extraction for Ship Detection from Multi-Resolution and Multi-Scene Synthetic Aperture Radar (SAR) Images
Authors: Gao Fei , Shi Wei , Wang Jun , Yang Erfu , Zhou Huiyu
Published: November 2019

Independent of daylight and weather conditions, synthetic aperture radar (SAR) images have been widely used for ship monitoring. The traditional methods for SAR ship detection are highly dependent on the statistical models of sea clutter or some predefined thresholds, and generally require a multi-step operation, which results in time-consuming and less robust ship detection. Recently, deep learning algorithms have found wide applications in ship detection from SAR images. However, due to the multi-resolution imaging mode and complex background, it is hard for the network to extract representative SAR target features, which limits the ship detection performance. In order to enhance the feature extraction ability of the network, three improvement techniques have been developed. Firstly, multi-level sparse optimization of SAR image is carried out to handle clutters and sidelobes so as to enhance the discrimination of the features of SAR images. Secondly, we hereby propose a novel split convolution block (SCB) to enhance the feature representation of small targets, which divides the SAR images into smaller sub-images as the input of the network. Finally, a spatial attention block (SAB) is embedded in the feature pyramid network (FPN) to reduce the loss of spatial information, during the dimensionality reduction process. In this paper, experiments on the multi-resolution SAR images of GaoFen-3 and Sentinel-1 under complex backgrounds are carried out and the results verify the effectiveness of SCB and SAB. The comparison results also show that the proposed method is superior to several state-of-the-art object detection algorithms.
Multispectral Image Super-Resolution Burned-Area Mapping Based on Space-Temperature Information
Authors: Wang Peng , Zhang Lei , Zhang Gong , Jin Benzhou , Leung Henry
Published: November 2019

Multispectral imaging (MI) provides important information for burned-area mapping. Due to the severe conditions of burned areas and the limitations of sensors, the resolution of collected multispectral images is sometimes very rough, hindering the accurate determination of burned areas. Super-resolution mapping (SRM) has been proposed for mapping burned areas in rough images to solve this problem, allowing super-resolution burned-area mapping (SRBAM). However, the existing SRBAM methods do not use sufficiently accurate space information and detailed temperature information. To improve the mapping accuracy of burned areas, an improved SRBAM method utilizing space–temperature information (STI) is proposed here. STI contains two elements, a space element and a temperature element. We utilized the random-walker algorithm (RWA) to characterize the space element, which encompassed accurate object space information, while the temperature element with rich temperature information was derived by calculating the normalized burn ratio (NBR). The two elements were then merged to produce an objective function with space–temperature information. The particle swarm optimization algorithm (PSOA) was employed to handle the objective function and derive the burned-area mapping results. The dataset of the Landsat-8 Operational Land Imager (OLI) from Denali National Park, Alaska, was used for testing and showed that the STI method is superior to the traditional SRBAM method.
Assessment of Night-Time Lighting for Global Terrestrial Protected and Wilderness Areas
Authors: Fan Liangxian , Zhao Jianjun , Wang Yeqiao , Ren Zhoupeng , Zhang Hongyan , Guo Xiaoyi
Published: November 2019

Protected areas (PAs) play an important role in biodiversity conservation and ecosystem integrity. However, human development has threatened and affected the function and effectiveness of PAs. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night-time stable light (NTL) data have proven to be an effective indicator of the intensity and change of human-induced urban development over a long time span and at a larger spatial scale. We used the NTL data from 1992 to 2013 to characterize the human-induced urban development and studied the spatial and temporal variation of the NTL of global terrestrial PAs. We selected seven types of PAs defined by the International Union for Conversation of Nature (IUCN), including strict nature reserve (Ia), wilderness area (Ib), national park (II), natural monument or feature (III), habitat/species management area (IV), protected landscape/seascape (V), and protected area with sustainable use of natural resources (VI). We evaluated the NTL digital number (DN) in PAs and their surrounding buffer zones, i.e., 0–1 km, 1–5 km, 5–10 km, 10–25 km, 25–50 km, and 50–100 km. The results revealed the level, growth rate, trend, and distribution pattern of NTL in PAs. Within PAs, areas of types V and Ib had the highest and lowest NTL levels, respectively. In the surrounding 1–100 km buffer zones, type V PAs also had the highest NTL level, but type VI PAs had the lowest NTL level. The NTL level in the areas surrounding PAs was higher than that within PAs. Types Ia and III PAs showed the highest and lowest NTL growth rate from 1992 to 2013, respectively, both inside and outside of PAs. The NTL distributions surrounding the Ib and VI PAs were different from other types. The areas close to Ib and VI boundaries, i.e., in the 0–25 km buffer zones, showed lower NTL levels, for which the highest NTL level was observed within the 25–100 km buffer zone. However, other types of PAs showed the opposite NTL patterns. The NTL level was lower in the distant buffer zones, and the lowest night light was within the 1–25 km buffer zones. Globally, 6.9% of PAs are being affected by NTL. Conditions of wilderness areas, e.g., high latitude regions, Tibetan Plateau, Amazon, and Caribbean, are the least affected by NTL. The PAs in Europe, Asia, and North America are more affected by NTL than South America, Africa, and Oceania.
Aircraft Target Classification for Conventional Narrow-Band Radar with Multi-Wave Gates Sparse Echo Data
Authors: Wang Wantian , Tang Ziyue , Chen Yichang , Zhang Yuanpeng , Sun Yongjian
Published: November 2019

For a conventional narrow-band radar system, the detectable information of the target is limited, and it is difficult for the radar to accurately identify the target type. In particular, the classification probability will further decrease when part of the echo data is missed. By extracting the target features in time and frequency domains from multi-wave gates sparse echo data, this paper presents a classification algorithm in conventional narrow-band radar to identify three different types of aircraft target, i.e., helicopter, propeller and jet. Firstly, the classical sparse reconstruction algorithm is utilized to reconstruct the target frequency spectrum with single-wave gate sparse echo data. Then, the micro-Doppler effect caused by rotating parts of different targets is analyzed, and the micro-Doppler based features, such as amplitude deviation coefficient, time domain waveform entropy and frequency domain waveform entropy, are extracted from reconstructed echo data to identify targets. Thirdly, the target features extracted from multi-wave gates reconstructed echo data are weighted and fused to improve the accuracy of classification. Finally, the fused feature vectors are fed into a support vector machine (SVM) model for classification. By contrast with the conventional algorithm of aircraft target classification, the proposed algorithm can effectively process sparse echo data and achieve higher classification probability via weighted features fusion of multi-wave gates echo data. The experiments on synthetic data are carried out to validate the effectiveness of the proposed algorithm.
Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry
Authors: Wei Haohan , He Xiufeng , Feng Yanming , Jin Shuanggen , Shen Fei
Published: November 2019

Snow is one of the most critical sources of freshwater, which influences the global water cycle and climate change. However, it is difficult to monitor global snow variations with high spatial–temporal resolution using traditional techniques due to their costly and labor-intensive nature. Nowadays, the Global Positioning System Interferometric Reflectometry (GPS-IR) technique can measure the average snow depth around a GPS antenna using its signal-to-noise ratio (SNR) data. Previous studies focused on the use of GPS data at sites located in flat areas or on very gentle slopes. In this contribution, we propose a strategy called the Tilted Surface Strategy (TSS), which uses the SNR data reflected only from the flat quadrants to estimate the snow depth instead of the conventional strategy, which employs all the SNR data reflected from the whole area around a GPS antenna. Three geodetic GPS sites from the Plate Boundary Observatory (PBO) project were chosen in this experimental study, of which GPS sites p683 and p101 were located on slopes with their gradients up to 18% and the site p025 was located on a flat area. Comparing the snow depths derived with the GPS-IR TSS method with the snow depth results provided with the GPS-PBO, i.e., GPS-IR with the conventional strategy, the Snowpack Telemetry (SNOTEL) network measurements and gridded Snow Data Assimilation System (SNODAS) estimates, it was found that the snow depths derived with the four methods had a good agreement, but the snow depth time series with the GPS-IR TSS method were closer to the SNOTEL measurements and the SNODAS estimates than those with GPS-PBO method. Similar observations were also obtained from the cumulative snowfall time series. Results generally indicated that for those GPS sites located on slopes, the TSS strategy works better.
A Low-Power High-Data-Transmission Multi-Lead ECG Acquisition Sensor System
Authors: Wang Liang-Hung , Zhang Wei , Guan Ming-Hui , Jiang Su-Ya , Fan Ming-Hui , Abu Patricia Angela R. , Chen Chiung-An , Chen Shih-Lun
Published: November 2019

This study presents a low-power multi-lead wearable electrocardiogram (ECG) signal sensor system design that can simultaneously acquire the electrocardiograms from three leads, I, II, and V1. The sensor system includes two parts, an ECG test clothing with five electrode patches and an acquisition device. Compared with the traditional 12-lead wired ECG detection instrument, which limits patient mobility and needs medical staff assistance to acquire the ECG signal, the proposed vest-type ECG acquisition system is very comfortable and easy to use by patients themselves anytime and anywhere, especially for the elderly. The proposed study incorporates three methods to reduce the power consumption of the system by optimizing the micro control unit (MCU) working mode, adjusting the radio frequency (RF) parameters, and compressing the transmitted data. In addition, Huffman lossless coding is used to compress the transmitted data in order to increase the sampling rate of the acquisition system. It makes the whole system operate continuously for a long period of time and acquire abundant ECG information, which is helpful for clinical diagnosis. Finally, a series of tests were performed on the designed wearable ECG device. The results have demonstrated that the multi-lead wearable ECG device can collect, process, and transmit ECG data through Bluetooth technology. The ECG waveforms collected by the device are clear, complete, and can be displayed in real-time on a mobile phone. The sampling rate of the proposed wearable sensor system is 250 Hz per lead, which is dependent on the lossless compression scheme. The device achieves a compression ratio of 2.31. By implementing a low power design on the device, the resulting overall operational current of the device is reduced by 37.6% to 9.87 mA under a supply voltage of 2.1 V. The proposed vest-type multi-lead ECG acquisition device can be easily employed by medical staff for clinical diagnosis and is a suitable wearable device in monitoring and nursing the off-ward patients.
A Distributed Approach for Estimating Battery State-Of-Charge in Solar Farms
Authors: Romero-Ternero MCarmen , Oviedo-Olmedo David , Carrasco Alejandro , Luque Joaquín
Published: November 2019

A common problem in solar farms is to predict when accumulators stop working optimally and start losing efficiency. This paper proposes and describes how to use Bayesian networks together with expert systems to predict this moment by using a telecontrol multiagent system for monitoring solar farms with distributed sensors, which was developed in a previous work. To this end, a Bayesian network model and its implementation are proposed. The resulting system meets the requirements of telecontrol systems (reliability, flexibility, and response time), yields a solution for the prediction of lifespan batteries, and provides the multiagent system with autonomous intelligent capabilities and integrated learning.
Distributed Rate-Control and Delay-Guaranteed Scheduling in MR-MC Wireless Mesh Networks
Authors: Li Liang , Zhao Xiongwen , Geng Suiyan , Zhang Yu
Published: November 2019

Wireless mesh networks (WMNs) can provide flexible wireless connections in smart city, Internet of Things (IoT), and device-to-device (D2D) communications. The performance of WMNs can be greatly enhanced by adopting the multi-radio multi-channel (MR-MC) technique, which enables a node to communicate with more nodes simultaneously. However, increasing the number of data flows will result in network congestion and longer end-to-end delays. In this paper, a distributed rate-control and delay-aware (DRDA) scheduling algorithm is proposed based on a multidimensional conflict graph. To satisfy the arrival rate and delay constraints of a flow, two virtual queues are constructed. All the actual and virtual queues are stabilized by the Lyapunov drift optimization method. The scheduling policy of each flow is optimized only based on the local information. The simulation results show that our proposed algorithm can maintain the stability of all the queues and strictly satisfy the arrival rate and delay constraint of each flow in the network as well.
Towards an Inertial Sensor-Based Wearable Feedback System for Patients after Total Hip Arthroplasty: Validity and Applicability for Gait Classification with Gait Kinematics-Based Features
Authors: Teufl Wolfgang , Taetz Bertram , Miezal Markus , Lorenz Michael , Pietschmann Juliane , Jöllenbeck Thomas , Fröhlich Michael , Bleser Gabriele
Published: November 2019

Patients after total hip arthroplasty (THA) suffer from lingering musculoskeletal restrictions. Three-dimensional (3D) gait analysis in combination with machine-learning approaches is used to detect these impairments. In this work, features from the 3D gait kinematics, spatio temporal parameters (Set 1) and joint angles (Set 2), of an inertial sensor (IMU) system are proposed as an input for a support vector machine (SVM) model, to differentiate impaired and non-impaired gait. The features were divided into two subsets. The IMU-based features were validated against an optical motion capture (OMC) system by means of 20 patients after THA and a healthy control group of 24 subjects. Then the SVM model was trained on both subsets. The validation of the IMU system-based kinematic features revealed root mean squared errors in the joint kinematics from 0.24° to 1.25°. The validity of the spatio-temporal gait parameters (STP) revealed a similarly high accuracy. The SVM models based on IMU data showed an accuracy of 87.2% (Set 1) and 97.0% (Set 2). The current work presents valid IMU-based features, employed in an SVM model for the classification of the gait of patients after THA and a healthy control. The study reveals that the features of Set 2 are more significant concerning the classification problem. The present IMU system proves its potential to provide accurate features for the incorporation in a mobile gait-feedback system for patients after THA.
Nitrogen-Doped Carbon Dots from Averrhoa carambola Fruit Extract as a Fluorescent Probe for Methyl Orange
Authors: Zulfajri Muhammad , Dayalan Sandhiya , Li Wang-Yu , Chang Chia-Jung , Chang Yuan-Pin , Huang Genin Gary
Published: November 2019

In this study, a simple and green hydrothermal treatment was performed to prepare nitrogen-doped carbon dots (NCDs) from Averrhoa carambola (AC) fruit extract as a carbon precursor and L-arginine (Arg) as a nitrogen dopant. The AC-NCDs were characterized by UV light, fluorescence spectroscopy, transmission electron microscopy, FTIR spectroscopy, Raman spectroscopy, UV-vis spectroscopy, and zeta potential analyzer. The AC-NCDs were spherical and the average diameter was estimated to be 6.67 nm. The AC-NCDs exhibited the maximum emission intensity at 446 nm with 360 nm excitation wavelength. The fluorescence quenching behavior of AC-NCDs after interacting with methyl orange (MO) dye was studied. The interaction of AC-NCDs and MO was achieved within 3 min and the fluorescence quenching was maintained to a fixed value even after 30 min. The linearity was obtained in the range of 1 to 25 μM MO with a 0.30 μM detection limit. Furthermore, the pH values affected the quenching behavior of the AC-NCDs/MO system where the interaction mechanisms were driven by the electrostatic interaction, π–π interaction, inner filter effect, and energy transfer. The pH 5 maintained higher quenching efficiency while other pH values slightly decreased the quenching efficiency. Incoming applications, the AC-NCDs can be used in various important fields, especially for environmental protection.
In-Line Monitoring and Control of Rheological Properties through Data-Driven Ultrasound Soft-Sensors
Authors: Tronci Stefania , Van Neer Paul , Giling Erwin , Stelwagen Uilke , Piras Daniele , Mei Roberto , Corominas Francesc , Grosso Massimiliano
Published: November 2019

The use of continuous processing is replacing batch modes because of their capabilities to address issues of agility, flexibility, cost, and robustness. Continuous processes can be operated at more extreme conditions, resulting in higher speed and efficiency. The issue when using a continuous process is to maintain the satisfaction of quality indices even in the presence of perturbations. For this reason, it is important to evaluate in-line key performance indicators. Rheology is a critical parameter when dealing with the production of complex fluids obtained by mixing and filling. In this work, a tomographic ultrasonic velocity meter is applied to obtain the rheological curve of a non-Newtonian fluid. Raw ultrasound signals are processed using a data-driven approach based on principal component analysis (PCA) and feedforward neural networks (FNN). The obtained sensor has been associated with a data-driven decision support system for conducting the process.