bluuebunny/crossref_metadata_2025 huggingface dataset:
Debottlenecking Thermophilic Cyanobacteria Cultivation and Harvesting through the Application of Inner-Light Photobioreactor and Chitosan
Authors: Zhang Hairuo , Chen Pengyu , Russel Mohammad , Tang Jie , Jin Peng , Daroch Maurycy
Published: July 2021

Thermophilic cyanobacteria are a low-carbon environmental resource with high potential thanks to their innate temperature tolerance and thermostable pigment, phycocyanin, which enhances light utilisation efficiency and generates a high-value product. However, large-scale cultivation and harvesting have always been bottlenecks in unicellular cyanobacteria cultivation due to their micrometric size. In this study, a 40-litre inner-light photobioreactor (PBR) was designed for scaled-up cultivation of Thermosynechococcus elongatus E542. By analysing light transmission and attenuation in the PBR and describing it via mathematical models, the supply of light energy to the reactor was optimised. It was found that the hyperbolic model describes the light attenuation characteristics of the cyanobacterial culture more accurately than the Lambert–Beer model. The internal illumination mode was applied for strain cultivation and showed a two-fold better growth rate and four-fold higher biomass concentration than the same strain grown in an externally illuminated photobioreactor. Finally, the downstream harvesting process was explored. A mixture of chitosan solutions was used as a flocculant to facilitate biomass collection. The effect of the following parameters on biomass harvesting was analysed: solution concentration, flocculation time and flocculant concentration. The analysis revealed that a 4 mg L−1 chitosan solution is optimal for harvesting the strain. The proposed solutions can improve large-scale cyanobacterial biomass cultivation and processing.
Morphological Analysis, Protein Profiling and Expression Analysis of Auxin Homeostasis Genes of Roots of Two Contrasting Cultivars of Rice Provide Inputs on Mechanisms Involved in Rice Adaptation towards Salinity Stress
Authors: Saini Shivani , Kaur Navdeep , Marothia Deeksha , Singh Baldev , Singh Varinder , Gantet Pascal , Pati Pratap Kumar
Published: July 2021

Plants remodel their root architecture in response to a salinity stress stimulus. This process is regulated by an array of factors including phytohormones, particularly auxin. In the present study, in order to better understand the mechanisms involved in salinity stress adaptation in rice, we compared two contrasting rice cultivars—Luna Suvarna, a salt tolerant, and IR64, a salt sensitive cultivar. Phenotypic investigations suggested that Luna Suvarna in comparison with IR64 presented stress adaptive root traits which correlated with a higher accumulation of auxin in its roots. The expression level investigation of auxin signaling pathway genes revealed an increase in several auxin homeostasis genes transcript levels in Luna Suvarna compared with IR64 under salinity stress. Furthermore, protein profiling showed 18 proteins that were differentially regulated between the roots of two cultivars, and some of them were salinity stress responsive proteins found exclusively in the proteome of Luna Suvarna roots, revealing the critical role of these proteins in imparting salinity stress tolerance. This included proteins related to the salt overly sensitive pathway, root growth, the reactive oxygen species scavenging system, and abscisic acid activation. Taken together, our results highlight that Luna Suvarna involves a combination of morphological and molecular traits of the root system that could prime the plant to better tolerate salinity stress.
Biotechnological Methods for Buckwheat Breeding
Authors: Luthar Zlata , Fabjan Primož , Mlinarič Katja
Published: July 2021

The Fagopyrum genus includes two cultivated species, namely common buckwheat (F. esculentum Moench) and Tartary buckwheat (F. tataricum Gaertn.), and more than 25 wild buckwheat species. The goal of breeders is to improve the properties of cultivated buckwheat with methods of classical breeding, with the support of biotechnological methods or a combination of both. In this paper, we reviewed the possibility to use transcriptomics, genomics, interspecific hybridization, tissue cultures and plant regeneration, molecular markers, genetic transformation, and genome editing to aid in both the breeding of buckwheat and in the identification and production of metabolites important for preserving human health. The key problems in buckwheat breeding are the unknown mode of inheritance of most traits, associated with crop yield and the synthesis of medicinal compounds, low seed yield, shedding of seeds, differential flowering and seed set on branches, and unknown action of genes responsible for the synthesis of buckwheat metabolites of pharmaceutical and medicinal interest.
Three Polymers from the Sea: Unique Structures, Directional Modifications, and Medical Applications
Authors: Wang Lei , Li Wenjun , Qin Song
Published: July 2021

With the increase of wounds and body damage, the clinical demand for antibacterial, hemostatic, and repairable biomaterials is increasing. Various types of biomedical materials have become research hotspots. Of these, and among materials derived from marine organisms, the research and application of alginate, chitosan, and collagen are the most common. Chitosan is mainly used as a hemostatic material in clinical applications, but due to problems such as the poor mechanical strength of a single component, the general antibacterial ability, and fast degradation speed research into the extraction process and modification mainly focuses on the improvement of the above-mentioned ability. Similarly, the research and modification of sodium alginate, used as a material for hemostasis and the repair of wounds, is mainly focused on the improvement of cell adhesion, hydrophilicity, degradation speed, mechanical properties, etc.; therefore, there are fewer marine biological collagen products. The research mainly focuses on immunogenicity removal and mechanical performance improvement. This article summarizes the source, molecular structure, and characteristics of alginate, chitosan, and collagen from marine organisms; and introduces the biological safety, clinical efficacy, and mechanism of action of these materials, as well as their extraction processes and material properties. Their modification and other issues are also discussed, and their potential clinical applications are examined.
Coloration and Multi-Functionalization of Polypropylene Fabrics with Selenium Nanoparticles
Authors: AbouElmaaty Tarek , Abdeldayem Shereen , Ramadan Shaimaa , Sayed-Ahmed Khaled , Plutino Maria
Published: July 2021

In this study, we developed a new approach for depositing selenium nanoparticles (SeNPs) into polypropylene (PP) fabrics via a one-step process under hydrothermal conditions by using an IR-dyeing machine to incorporate several functionalities, mainly coloration, antibacterial activity and ultraviolet (UV) protection. The formation, size distribution, and dispersion of the SeNPs were determined using X-ray diffraction (XRD), ultraviolet-visible (UV/Vis), transmission electron microscopy (TEM) and the color strength, fastness, antibacterial properties, and UV protection of the treated fabrics were also explored. The UV-Vis spectra and TEM analysis confirmed the synthesis of spherical well-dispersed SeNPs and the XRD analysis showed the successful deposition of SeNPs into PP fabrics. The obtained results demonstrate that the SeNPs-PP fabrics is accompanied by a noticeable enhancement in measurements of color strength, fastness, and UV-protection factor (UPF), as well as excellent antibacterial activity. Viability studies showed that SeNPs-PP fabrics are non-toxic against wi-38cell line. In addition, the treated SeNPs-PP fabrics showed an increase in conductivity. The obtained multifunctional fabrics are promising for many industrial applications such as the new generation of curtains, medical fabrics, and even automotive interior parts.
Structural and Rheological Properties of Nonedible Vegetable Oil-Based Resin
Authors: Mudri Nurul Huda , Abdullah Luqman Chuah , Aung Min Min , Biak Dayang Radiah Awang , Tajau Rida
Published: July 2021

Jatropha oil-based polyol (JOL) was prepared from crude Jatropha oil via an epoxidation and hydroxylation reaction. During the isocyanation step, two different types of diisocyanates; 2,4-toluene diisocyanate (2,4-TDI) and isophorone diisocyanate (IPDI), were introduced to produce Jatropha oil-based polyurethane acrylates (JPUA). The products were named JPUA-TDI and JPUA-IPDI, respectively. The success of the stepwise reactions of the resins was confirmed using 1H nuclear magnetic resonance (NMR) spectroscopy to support the Fourier-transform infrared (FTIR) spectroscopy analysis that was reported in the previous study. For JPUA-TDI, the presence of a signal at 7.94 ppm evidenced the possible side reactions between urethane linkages with secondary amine that resulted in an aryl-urea group (Ar-NH-COO-). Meanwhile, the peak of 2.89 ppm was assigned to the α-position of methylene to the carbamate (-CH2NHCOO) group in the JPUA-IPDI. From the rheological study, JO and JPUA-IPDI in pure form were classified as Newtonian fluids, while JPUA-TDI showed non-Newtonian behaviour with pseudoplastic or shear thinning behaviour at room temperature. At elevated temperatures, the JO, JPUA-IPDI mixture and JPUA-TDI mixture exhibited reductions in viscosity and shear stress as the shear rate increased. The JO and JPUA-IPDI mixture maintained Newtonian fluid behaviour at all temperature ranges. Meanwhile, the JPUA-TDI mixture showed shear thickening at 25 °C and shear thinning at 40 °C, 60 °C and 80 °C. The master curve graph based on the shear rate for the JO, JPUA-TDI mixture and JPUA-IPDI mixture at 25 °C, 40 °C, 60 °C and 80 °C was developed as a fluid behaviour reference for future storage and processing conditions during the encapsulation process. The encapsulation process can be conducted to fabricate a self-healing coating based on a microcapsule triggered either by air or ultra-violet (UV) radiation.
Natural Fibers as an Alternative to Synthetic Fibers in Reinforcement of Geopolymer Matrices: A Comparative Review
Authors: de Azevedo Afonso , Cruz Ariana , Marvila Markssuel , de Oliveira Leandro , Monteiro Sergio , Vieira Carlos , Fediuk Roman , Timokhin Roman , Vatin Nikolai , Daironas Marina
Published: July 2021

Geopolymer materials have been gaining ground in the civil construction sector not only for having superior physical properties when compared to conventional cement, but also for being less harmful to the environment, since the synthesis of the geopolymer does not release toxic gases or require high energy costs. On the other hand, geopolymer materials like cementitious matrices have low flexural strength and have fragile breakage. To overcome these deficiencies, the insertion of fibers in geopolymeric matrices has been evaluated as a solution. Although most research on this practice focuses on the use of synthetic fibers, the use of natural fibers has been growing and brings as an advantage the possibility of producing an even more ecological material, satisfying the need to create eco-friendly materials that exists today in society. Thus, this paper aimed to, through the evaluation of research available in the literature, understand the behavior of fibers in geopolymer matrices, identify similarities and differences between the performance of geopolymer composites reinforced with natural and synthetic fibers and, understanding that it is possible, point out ways to optimize the performance of these composites.
Intra-Soil Milling for Stable Evolution and High Productivity of Kastanozem Soil
Authors: Kalinitchenko Valery Petrovich , Glinushkin Alexey Pavlovich , Sharshak Vladimir Konstantinovich , Ladan Evgene Panteleimonovich , Minkina Tatiana Mikhailovna , Sushkova Svetlana Nikolaevna , Mandzhieva Saglara Sergeevna , Batukaev Abdulmalik Abdulkhamidovich , Chernenko Vladimir Vladimirovich , Ilyina Ljudmila Pavlovna , Kosolapov Vladimir Mikhailovich , Barbashev Andrei Igorevich , Antonenko Elena Mikhailovna
Published: July 2021

The long-term field experiment on the Kastanozem showed that the standard moldboard plowing to a depth of 22 cm (control), chiseling to a depth of 35 cm, and three-tier plowing (machine type PTN–40) to a depth of 45 cm was incapable of providing a stable soil structure and aggregate system. The transcendental Biogeosystem Technique (BGT*) methodology for intra-soil milling of the 20–45 cm layer and the intra-soil milling PMS–70 machine were developed. The PMS–70 soil processing provided the content of 1–3 mm sized aggregate particle fraction in the illuvial horizon of about 50 to 60%, which was 3-fold higher compared to standard plowing systems. Soil bulk density reduced in the layer 20–40 cm to 1.35 t m−3 compared to 1.51 t m−3 in the control option. In the control, the rhizosphere developed only in the soil upper layer. There were 1.3 roots per cm2 in 0–20 cm, and 0.2 roots per cm2 in 20–40 cm. The rhizosphere spreads only through the soil crevices after chilling. After three-tier plowing (PTN–40), the rhizosphere developed better in the local comfort zones of the soil profile between soil blocks impermeable for roots. After intra-soil milling PMS–70, the rhizosphere developed uniformly in the whole soil profile: 2.2 roots per cm2 in 0–20 cm; 1.7 roots per cm2 in 20–40 cm. Matric water potential was higher, soil salinization was lower, and the pH was close to neutral. Soil organic matter (SOM) content increased to 3.3% in 0–20 cm and 2.1% in 20–40 cm compared to the control (2.0% in the 0–20 cm soil layer and 1.3% in the 20–40 cm layer). The spring barley yield was 53% higher compared to the control. The technology life cycle profitability was moldboard 21.5%, chiseling 6.9%, three-tier 15.6%, and intra-soil milling 45.6%. The new design of the intra-soil milling machine provides five times less traction resistance and 80% increased reliability, halving energy costs.
Untangling the “Unwritten Documents” of the Prophet Muḥammad. An Isnād-cum-Matn Analysis of Interwoven Traditions
Authors: Boekhoff-van der Voort Nicolet
Published: July 2021

Since the earliest studies of Islam by non-Muslims were carried out, variant traditions (aḥādīth) have been regarded as a proof of forgery or editing within the ḥadīth material. Early studies have shown that variances are the result of different processes, some intentionally and others mistakenly; some caused by editing processes, while others through the process of transmission across the first centuries of Islam. During the transmission process, or the genesis of a tradition, accounts are constantly shaped and adjusted. The use of topoi forms a part of this process as well as the inclusion of motifs in different accounts. The present article will explore one of these motifs, specifically, the instruction of the Prophet Muḥammad, on his deathbed, to bring him writing materials so that he could prepare a document for his community. This motif appears in a number of accounts with different settings, characters and details on the nature of the document itself. This article examines whether there exists a direct relationship between the different accounts and, if so, what does this mean. Through this study, we will see that additional motifs have been added to this tradition during its transmission process and that some of these motifs can be attributed to regionalisation or specific transmitters.
Ten Years of SNPP VIIRS Reflective Solar Bands On-Orbit Calibration and Performance
Authors: Sun Junqiang , Xiong Xiaoxiong , Lei Ning , Li Sherry , Twedt Kevin , Angal Amit
Published: July 2021

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) has successfully operated on-orbit for nearly ten years since its launch in October 2011, continuously making global observations and improving studies of changes in the Earth’s climate and environment. VIIRS has 22 spectral bands, among which 14 are reflective solar bands (RSBs) covering a spectral range from 0.41 to 2.25 μm. The SNPP VIIRS RSBs are primarily calibrated by the onboard solar diffuser (SD), with its on-orbit degradation tracked by an onboard SD stability monitor (SDSM). The near-monthly scheduled lunar observations, together with the sensor responses over stable ground targets, have contributed to the sensor’s mission-long on-orbit calibration and characterization. Numerous improvements have been made in the RSB calibration methodology since SNPP VIIRS was launched, and the RSB calibration has reached a mature stage after almost ten years of on-orbit operation. SNPP is a joint NASA/NOAA mission and there are two teams, the NASA VIIRS Calibration Support Team (VCST) and the NOAA VIIRS Sensor Data Record Team, which are dedicated to SNPP VIIRS on-orbit calibration. In this paper, we focus on the calibration performed by the NASA VCST. The SNPP VIIRS RSB calibration methodologies used to produce the calibration coefficient look up tables for the latest NASA Level 1B Collection 2 products are reviewed and the calibration improvements incorporated in this collection are described. Recent calibration changes include the removal of image striping caused by non-uniform degradation of the SD, improvements to the method for combining lunar and SD data, mitigation of the effects due a recent anomaly in the SD measurements, estimation of the SD degradation beyond 935 nm, and fitting strategy improvements for look-up table delivery. Overall, the SNPP VIIRS RSBs have performed well since its launch and continue to meet design specifications.
Snow Cover Variability in the Greater Alpine Region in the MODIS Era (2000–2019)
Authors: Fugazza Davide , Manara Veronica , Senese Antonella , Diolaiuti Guglielmina , Maugeri Maurizio
Published: July 2021

Snow cover is particularly important in the Alps for tourism and the production of hydroelectric energy. In this study, we investigate the spatiotemporal variability in three snow cover metrics, i.e., the length of season (LOS), start of season (SOS) and end of season (EOS), obtained by gap-filling of MOD10A1 and MYD10A1, daily snow cover products of MODIS (Moderate-resolution Imaging Spectroradiometer). We analyze the period 2000–2019, evaluate snow cover patterns in the greater Alpine region (GAR) as a whole and further subdivide it into four subregions based on geographical and climate divides to investigate the drivers of local variability. We found differences both in space and time, with the northeastern region having generally the highest LOS (74 ± 4 days), compared to the southern regions, which exhibit a much shorter snow duration (48/49 ± 2 days). Spatially, the variability in LOS and the other metrics is clearly related to elevation (r2 = 0.85 for the LOS), while other topographic (slope, aspect and shading) and geographic variables (latitude and longitude) play a less important role at the MODIS scale. A high interannual variability was also observed from 2000 to 2019, as the average LOS in the GAR ranged between 41 and 85 days. As a result of high variability, no significant trends in snow cover metrics were seen over the GAR when considering all grid cells. Considering 500-m elevation bands and subregions, as well as individual grid points, we observed significant negative trends above 3000 m a.s.l., with an average of −17 days per decade. While some trends appeared to be caused by glacierized areas, removing grid cells covered by glaciers leads to an even higher frequency of grid cells with significant trends above 3000 m a.s.l., reaching 100% at 4000 m a.s.l. Trends are however to be considered with caution because of the limited length of the observation period.
Phenological Classification Using Deep Learning and the Sentinel-2 Satellite to Identify Priority Afforestation Sites in North Korea
Authors: Kim Joon , Lim Chul-Hee , Jo Hyun-Woo , Lee Woo-Kyun
Published: July 2021

The role of forests to sequester carbon is considered an important strategy for mitigating climate change and achieving net zero emissions. However, forests in North Korea have continued to be cleared since the 1990s due to the lack of food and energy resources. Deforestation in this country has not been accurately classified nor consistently reported because of the characteristics of small patches. This study precisely determined the area of deforested land in North Korea through the vegetation phenological classification using high-resolution satellite imagery and deep learning algorithms. Effective afforestation target sites in North Korea were identified with priority grade. The U-Net deep learning algorithm and time-series Sentinel-2 satellite images were applied to phenological classification; the results reflected the small patch-like characteristics of deforestation in North Korea. Based on the phenological classification, the land cover of the country was classified with an accuracy of 84.6%; this included 2.6 million ha of unstocked forest and reclaimed forest. Sites for afforestation were prioritized into five grades based on deforested characteristics, altitude and slope. Forest area is expanded and the forest ecosystem is restored through successful afforestation, this may improve the overall ecosystem services in North Korea. In the long term, it will be possible to contribute to carbon neutrality and greenhouse gas reduction on the Korean Peninsula level through optimal afforestation by using these outcomes.
The Process-Mode-Driving Force of Cropland Expansion in Arid Regions of China Based on the Land Use Remote Sensing Monitoring Data
Authors: Cai Tianyi , Zhang Xinhuan , Xia Fuqiang , Zhang Zhiping , Yin Jingjing , Wu Shengqin
Published: July 2021

The center of gravity of China’s new cropland has shifted from Northeast China to the Xinjiang oasis areas where the ecological environment is relatively fragile. However, we currently face a lack of a comprehensive review of the cropland expansion in oasis areas of Xinjiang, which is importantly associated with the sustainable use of cropland, social stability and oasis ecological security. In this study, the land use remote sensing monitoring data in 1990, 2000, 2010 and 2018 were used to comprehensively analyze the process characteristics, different modes and driving mechanisms of the cropland expansion in Xinjiang, as well as its spatial heterogeneity at the oasis area level. The results revealed that cropland in Xinjiang continued to expand from 5803 thousand hectares in 1990 to 8939 thousand hectares in 2018 and experienced three stages of expansion: steady expansion, rapid expansion, and slow expansion. The center of gravity of cropland showed the characteristic of shifting to the South. Edge expansion and encroachment on grassland were the dominant spatial pattern mode and land use conversion mode of Xinjiang’s cropland expansion, respectively. The expansion of cropland in Xinjiang was affected by multiple factors. Irrigation conditions played a dominant role. Topography indirectly affected cropland expansion by affecting the suitability of agricultural production and development. Population growth and farmers’ income were important driving forces. There was significant spatial heterogeneity in the intensity, mode and driving force of cropland expansion among different oasis areas in Xinjiang. The spatial shift of China’s new cropland has occupied a large amount of water resources and ecological land in Xinjiang and exacerbated the vulnerability of the ecosystem in arid regions. The key to sustainable management of cropland in Xinjiang in the future lies in maintaining an appropriate scale of cropland and promoting the coordinated development of cropland, population, water resources and industry.
Global Land Cover Assessment Using Spatial Uniformity Validation Dataset
Authors: Ishii Yoshie , Iwao Koki , Kinoshita Tsuguki
Published: July 2021

The Degree Confluence Project (DCP) is a volunteer-based validation dataset that comprises useful information for global land cover map validation. However, there is a problem with using DCP points as validation data for the accuracy assessment of land cover maps. While resolutions of typical global land cover maps are several hundred meters to several kilometers, DCP points can only guarantee an area of several tens of meters that can be confirmed by ground photographs. So, the objective of this study is to create a land cover map validation dataset with added spatial uniformity information using satellite images and DCP points. For this, we devised a new method to semiautomatically guarantee the spatial uniformity of DCP validation data points at any resolution. This method can judge the validation data with guaranteed uniformity with a user’s accuracy of 0.954. Furthermore, we conducted the accuracy assessment for the existing global land cover maps by the DCP validation data with guaranteed spatial uniformity and found that the trends differed by class and region.
Detection and Tracking of Pedestrians Using Doppler LiDAR
Authors: Peng Xiaoyi , Shan Jie
Published: July 2021

Pedestrian detection and tracking is necessary for autonomous vehicles and traffic management. This paper presents a novel solution to pedestrian detection and tracking for urban scenarios based on Doppler LiDAR that records both the position and velocity of the targets. The workflow consists of two stages. In the detection stage, the input point cloud is first segmented to form clusters, frame by frame. A subsequent multiple pedestrian separation process is introduced to further segment pedestrians close to each other. While a simple speed classifier is capable of extracting most of the moving pedestrians, a supervised machine learning-based classifier is adopted to detect pedestrians with insignificant radial velocity. In the tracking stage, the pedestrian’s state is estimated by a Kalman filter, which uses the speed information to estimate the pedestrian’s dynamics. Based on the similarity between the predicted and detected states of pedestrians, a greedy algorithm is adopted to associate the trajectories with the detection results. The presented detection and tracking methods are tested on two data sets collected in San Francisco, California by a mobile Doppler LiDAR system. The results of the pedestrian detection demonstrate that the proposed two-step classifier can improve the detection performance, particularly for detecting pedestrians far from the sensor. For both data sets, the use of Doppler speed information improves the F1-score and the recall by 15% to 20%. The subsequent tracking from the Kalman filter can achieve 83.9–55.3% for the multiple object tracking accuracy (MOTA), where the contribution of the speed measurements is secondary and insignificant.
Multiscale Hydrogeomorphometric Analysis for Fluvial Risk Management. Application in the Carrión River, Spain
Authors: Lombana Lorena , Martínez-Graña Antonio
Published: July 2021

The sustainable management of fluvial systems requires reliable knowledge of the mechanisms that control the basins and their drainages, which in turn must be prioritized for the application of measures for flood-risk reduction. Thus, given the need to develop methodological frameworks capable of integrating remote sensing technologies at different scales, as well as traditional metrics and anthropic variables, in this study, a multiscale method is proposed for the characterization and prioritization of river stretches for fluvial risk management. This methodology involves the study of drivers at the watershed level, and a detailed morphometric and hydrogeomorphological analysis of the main channel for fluvial landscape classification, segmentation, and aggregation into units, considering also anthropic variables. Therefore, it includes the use of LiDAR data and exploration GIS tools, whose results are corroborated through fieldwork, where ephemeral and topographic evidence of fluvial dynamics are collected. The procedure is validated in the Carrión river basin, Palencia, Spain, where a high degree of maturity and geomorphological development are determined. Hence, the main channel can be classified into eight geomorphic units and divided into homogeneous segments, which, according to categorical elements such as urban interventions, are prioritized, obtaining, as a result, six stretches of main interest for river risk management.
An Integrated Horizon Picking Method for Obtaining the Main and Detailed Reflectors on Sub-Bottom Profiler Sonar Image
Authors: Li Shaobo , Zhao Jianhu , Zhang Hongmei , Qu Siheng
Published: July 2021

A sub-bottom profiler (SBP) can capture the sediment interfaces and properties of different types of sediment. Horizon picking from SBP images is one of the most crucial steps in marine sub-bottom sediment interpretation. However, traditional horizon picking methods are good at obtaining the main horizons representing the main reflectors while ignoring the detailed horizons. While detailed horizons are the prime objective, many tiny structures caused by interference echoes will also be picked. To overcome this limitation, an integrated horizon picking method for obtaining the main and detailed horizons simultaneously is proposed in this paper. A total of three main process steps: the diffusion filtering method, the enhancement filtering method as well as the local phase calculation method, are used to help obtain the main and detailed horizons. The diffusion filtering method smooths the SBP images and preserves reflectors. Enhancement filtering can eliminate outliers and enhance reflectors. The local phase can be used to highlight all of the reflections and help in the choosing of detailed horizons. A series of experiments were then performed to validate the effectiveness of the proposed method, and good performances were achieved.
Cloud Cover throughout All the Paddy Rice Fields in Guangdong, China: Impacts on Sentinel 2 MSI and Landsat 8 OLI Optical Observations
Authors: Jiang Rui , Sanchez-Azofeifa Arturo , Laakso Kati , Xu Yan , Zhou Zhiyan , Luo Xiwen , Huang Junhao , Chen Xin , Zang Yu
Published: July 2021

Cloud cover hinders the effective use of vegetation indices from optical satellite-acquired imagery in cloudy agricultural production areas, such as Guangdong, a subtropical province in southern China which supports two-season rice production. The number of cloud-free observations for the earth-orbiting optical satellite sensors must be determined to verify how much their observations are affected by clouds. This study determines the quantified wide-ranging impact of clouds on optical satellite observations by mapping the annual total observations (ATOs), annual cloud-free observations (ACFOs), monthly cloud-free observations (MCFOs) maps, and acquisition probability (AP) of ACFOs for the Sentinel 2 (2017–2019) and Landsat 8 (2014–2019) for all the paddy rice fields in Guangdong province (APRFG), China. The ATOs of Landsat 8 showed relatively stable observations compared to the Sentinel 2, and the per-field ACFOs of Sentinel 2 and Landsat 8 were unevenly distributed. The MCFOs varied on a monthly basis, but in general, the MCFOs were greater between August and December than between January and July. Additionally, the AP of usable ACFOs with 52.1% (Landsat 8) and 47.7% (Sentinel 2) indicated that these two satellite sensors provided markedly restricted observation capability for rice in the study area. Our findings are particularly important and useful in the tropics and subtropics, and the analysis has described cloud cover frequency and pervasiveness throughout different portions of the rice growing season, providing insight into how rice monitoring activities by using Sentinel 2 and Landsat 8 imagery in Guangdong would be impacted by cloud cover.
Remote Sensing Estimation of Bamboo Forest Aboveground Biomass Based on Geographically Weighted Regression
Authors: Wang Jingyi , Du Huaqiang , Li Xuejian , Mao Fangjie , Zhang Meng , Liu Enbin , Ji Jiayi , Kang Fangfang
Published: July 2021

Bamboo forests are widespread in subtropical areas and are well known for their rapid growth and great carbon sequestration ability. To recognize the potential roles and functions of bamboo forests in regional ecosystems, forest aboveground biomass (AGB)—which is closely related to forest productivity, the forest carbon cycle, and, in particular, carbon sinks in forest ecosystems—is calculated and applied as an indicator. Among the existing studies considering AGB estimation, linear or nonlinear regression models are the most frequently used; however, these methods do not take the influence of spatial heterogeneity into consideration. A geographically weighted regression (GWR) model, as a spatial local model, can solve this problem to a certain extent. Based on Landsat 8 OLI images, we use the Random Forest (RF) method to screen six variables, including TM457, TM543, B7, NDWI, NDVI, and W7B6VAR. Then, we build the GWR model to estimate the bamboo forest AGB, and the results are compared with those of the cokriging (COK) and orthogonal least squares (OLS) models. The results show the following: (1) The GWR model had high precision and strong prediction ability. The prediction accuracy (R2) of the GWR model was 0.74, 9%, and 16% higher than the COK and OLS models, respectively, while the error (RMSE) was 7% and 12% lower than the errors of the COK and OLS models, respectively. (2) The bamboo forest AGB estimated by the GWR model in Zhejiang Province had a relatively dense spatial distribution in the northwestern, southwestern, and northeastern areas. This is in line with the actual bamboo forest AGB distribution in Zhejiang Province, indicating the potential practical value of our study. (3) The optimal bandwidth of the GWR model was 156 m. By calculating the variable parameters at different positions in the bandwidth, close attention is given to the local variation law in the estimation of the results in order to reduce the model error.
Angle Estimation for MIMO Radar in the Presence of Gain-Phase Errors with One Instrumental Tx/Rx Sensor: A Theoretical and Numerical Study
Authors: Wen Fangqing , Shi Junpeng , Wang Xinhai , Wang Lin
Published: July 2021

Ideal transmitting and receiving (Tx/Rx) array response is always desirable in multiple-input multiple-output (MIMO) radar. In practice, nevertheless, Tx/Rx arrays may be susceptible to unknown gain-phase errors (GPE) and yield seriously decreased positioning accuracy. This paper focuses on the direction-of-departure (DOD) and direction-of-arrival (DOA) problem in bistatic MIMO radar with unknown gain-phase errors (GPE). A novel parallel factor (PARAFAC) estimator is proposed. The factor matrices containing DOD and DOA are firstly obtained via PARAFAC decomposition. One DOD-DOA pair estimation is then accomplished from the spectrum searching. Thereafter, the remainder DOD and DOA are achieved by the least squares technique with the previous estimated angle pair. The proposed estimator is analyzed in detail. It only requires one instrumental Tx/Rx sensor, and it outperforms the state-of-the-art algorithms. Numerical simulations verify the theoretical advantages.
Three-Dimensional Interferometric ISAR Imaging Algorithm Based on Cross Coherence Processing
Authors: Lv Qian , Zhang Shaozhe
Published: July 2021

Interferometric inverse synthetic aperture radar (InISAR) has received significant attention in three-dimensional (3D) imaging due to its applications in target classification and recognition. The traditional two-dimensional (2D) ISAR image can be interpreted as a filtered projection of a 3D target’s reflectivity function onto an image plane. Such a plane usually depends on unknown radar-target geometry and dynamics, which results in difficulty interpreting an ISAR image. Using the L-shape InISAR imaging system, this paper proposes a novel 3D target reconstruction algorithm based on Dechirp processing and 2D interferometric ISAR imaging, which can jointly estimate the effective rotation vector and the height of scattering center. In order to consider only the areas of the target with meaningful interferometric phase and mitigate the effects of noise and sidelobes, a special cross-channel coherence-based detector (C3D) is introduced. Compared to the multichannel CLEAN technique, advantages of the C3D include the following: (1) the computational cost is lower without complex iteration and (2) the proposed method, which can avoid propagating errors, is more suitable for a target with multi-scattering points. Moreover, misregistration and its influence on target reconstruction are quantitatively discussed. Theoretical analysis and numerical simulations confirm the suitability of the algorithm for 3D imaging of multi-scattering point targets with high efficiency and demonstrate the reliability and effectiveness of the proposed method in the presence of noise.
Scalable Data Model for Traffic Congestion Avoidance in a Vehicle to Cloud Infrastructure
Authors: Stan Ioan , Suciu Vasile , Potolea Rodica
Published: July 2021

Traffic congestion experience in urban areas has negative impact on our daily lives by consuming our time and resources. Intelligent Transportation Systems can provide the necessary infrastructure to mitigate such challenges. In this paper, we propose a novel and scalable solution to model, store and control traffic data based on range query data structures (K-ary Interval Tree and K-ary Entry Point Tree) which allows data representation and handling in a way that better predicts and avoids traffic congestion in urban areas. Our experiments, validation scenarios, performance measurements and solution assessment were done on Brooklyn, New York traffic congestion simulation scenario and shown the validity, reliability, performance and scalability of the proposed solution in terms of time spent in traffic, run-time and memory usage. The experiments on the proposed data structures simulated up to 10,000 vehicles having microseconds time to access traffic information and below 1.5 s for congestion free route generation in complex scenarios. To the best of our knowledge, this is the first scalable approach that can be used to predict urban traffic and avoid congestion through range query data structure traffic modelling.
Ex-Vivo Measurement of the pH in Aqueous Humor Samples by a Tapered Fiber-Optic Sensor
Authors: Podrazký Ondřej , Mrázek Jan , Proboštová Jana , Vytykáčová Soňa , Kašík Ivan , Pitrová Šárka , Jasim Ali A.
Published: July 2021

A practical demonstration of pH measurement in real biological samples with an in-house developed fiber-optic pH sensor system is presented. The sensor uses 8-hydroxypyrene-1,3,6-trisulfonate (HPTS) fluorescent dye as the opto-chemical transducer. The dye is immobilized in a hybrid sol-gel matrix at the tip of a tapered optical fiber. We used 405 nm and 450 nm laser diodes for the dye excitation and a photomultiplier tube as a detector. The sensor was used for the measurement of pH in human aqueous humor samples during cataract surgery. Two groups of patients were tested, one underwent conventional phacoemulsification removal of the lens while the other was subjected to femtosecond laser assisted cataract surgery (FLACS). The precision of the measurement was ±0.04 pH units. The average pH of the aqueous humor of patients subjected to FLACS and those subjected to phacoemulsification were 7.24 ± 0.17 and 7.31 ± 0.20 respectively.
Atypical Gait Cycles in Parkinson’s Disease
Authors: Ghislieri Marco , Agostini Valentina , Rizzi Laura , Knaflitz Marco , Lanotte Michele
Published: July 2021

It is important to find objective biomarkers for evaluating gait in Parkinson’s Disease (PD), especially related to the foot and lower leg segments. Foot-switch signals, analyzed through Statistical Gait Analysis (SGA), allow the foot-floor contact sequence to be characterized during a walking session lasting five-minutes, which includes turnings. Gait parameters were compared between 20 PD patients and 20 age-matched controls. PDs showed similar straight-line speed, cadence, and double-support compared to controls, as well as typical gait-phase durations, except for a small decrease in the flat-foot contact duration (−4% of the gait cycle, p = 0.04). However, they showed a significant increase in atypical gait cycles (+42%, p = 0.006), during both walking straight and turning. A forefoot strike, instead of a “normal” heel strike, characterized the large majority of PD’s atypical cycles, whose total percentage was 25.4% on the most-affected and 15.5% on the least-affected side. Moreover, we found a strong correlation between the atypical cycles and the motor clinical score UPDRS-III (r = 0.91, p = 0.002), in the subset of PD patients showing an abnormal number of atypical cycles, while we found a moderate correlation (r = 0.60, p = 0.005), considering the whole PD population. Atypical cycles have proved to be a valid biomarker to quantify subtle gait dysfunctions in PD patients.
Accuracy and Uncertainty of Gradient Based Leak Localization Procedure for Liquid Transmission Pipelines
Authors: Ostapkowicz Pawel , Bratek Andrzej
Published: July 2021

This paper describes issues of leakage localization in liquid transmission pipelines. It focuses on the standard leak localization procedure, which is based on the calculation of pressure gradients using pressure measurements captured along a pipeline. The procedure was verified in terms of an accuracy and uncertainty assessment of the resultant coordinate of a leak spot. An important aim of the verification was to assess the effectiveness of the procedure in the case of localization of low intensity leakages with a level of 0.25–2.00% of the nominal flow rate. An uncertainty assessment was carried out according to the GUM convention. The assessment was based on the metrological characteristics of measuring devices and measurement data obtained from the laboratory model of the pipeline.
Microneedle Array Electrode-Based Wearable EMG System for Detection of Driver Drowsiness through Steering Wheel Grip
Authors: Satti Afraiz Tariq , Kim Jiyoun , Yi Eunsurk , Cho Hwi-young , Cho Sungbo
Published: July 2021

Driver drowsiness is a major cause of fatal accidents throughout the world. Recently, some studies have investigated steering wheel grip force-based alternative methods for detecting driver drowsiness. In this study, a driver drowsiness detection system was developed by investigating the electromyography (EMG) signal of the muscles involved in steering wheel grip during driving. The EMG signal was measured from the forearm position of the driver during a one-hour interactive driving task. Additionally, the participant’s drowsiness level was also measured to investigate the relationship between muscle activity and driver’s drowsiness level. Frequency domain analysis was performed using the short-time Fourier transform (STFT) and spectrogram to assess the frequency response of the resultant signal. An EMG signal magnitude-based driver drowsiness detection and alertness algorithm is also proposed. The algorithm detects weak muscle activity by detecting the fall in EMG signal magnitude due to an increase in driver drowsiness. The previously presented microneedle electrode (MNE) was used to acquire the EMG signal and compared with the signal obtained using silver-silver chloride (Ag/AgCl) wet electrodes. The results indicated that during the driving task, participants’ drowsiness level increased while the activity of the muscles involved in steering wheel grip decreased concurrently over time. Frequency domain analysis showed that the frequency components shifted from the high to low-frequency spectrum during the one-hour driving task. The proposed algorithm showed good performance for the detection of low muscle activity in real time. MNE showed highly comparable results with dry Ag/AgCl electrodes, which confirm its use for EMG signal monitoring. The overall results indicate that the presented method has good potential to be used as a driver’s drowsiness detection and alertness system.
Nonlinear Guided-Wave Mixing for Condition Monitoring of Bolted Joints
Authors: Pineda Allen Juan Carlos , Ng Ching Tai
Published: July 2021

Bolted joints are fundamental to numerous structural components in engineering practice. Nevertheless, their failure or even their loosening can lead to insufficient performance and reduced structural safety. This study presents a theoretical development and experimental investigation into nonlinear guided-wave mixing for integrity monitoring of bolted joints in plates. Combinational harmonics generated due to nonlinear Lamb wave mixing and contact acoustic nonlinearity at the bolted joints were used to evaluate the applied torque level in the joint. The area of the power spectral density in the region of the sum combinational harmonic bandwidth is found to be highly correlated to the applied torque level at the joint. Moreover, the effect of the number of cycles and thus the time duration of the excitation is investigated. The results show that the combinational harmonics remain robust for different numbers of cycles in detecting bolt loosening. The findings presented in this study also provide physical insight into the phenomena of nonlinear Lamb wave mixing for evaluating applied torque in bolted joints, and the results help further advance the use of nonlinear guided waves for damage detection.
MobChain: Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus
Authors: Zafar Faheem , Khan Abid , Malik Saif Ur Rehman , Ahmed Mansoor , Maple Carsten , Anjum Adeel
Published: July 2021

Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). However, a user’s full control over a smart device can allow tampering of the location proof. Witness-oriented location proof systems (LPS) have emerged to resist the generation of false proofs and mitigate collusion attacks. However, witness-oriented LPS are still susceptible to three-way collusion attacks (involving the user, location authority, and the witness). To overcome the threat of three-way collusion in existing schemes, we introduce a decentralized consensus protocol called MobChain in this paper. In this scheme the selection of a witness and location authority is achieved through a distributed consensus of nodes in an underlying P2P network that establishes a private blockchain. The persistent provenance data over the blockchain provides strong security guarantees; as a result, the forging and manipulation of location becomes impractical. MobChain provides secure location provenance architecture, relying on decentralized decision making for the selection of participants of the protocol thereby addressing the three-way collusion problem. Our prototype implementation and comparison with the state-of-the-art solutions show that MobChain is computationally efficient and highly available while improving the security of LPS.