bluuebunny/crossref_metadata_2025 huggingface dataset:
Flexible Sensory Systems: Structural Approaches
Authors: Park Chan , Lee Byeongjun , Kim Jungmin , Lee Haran , Kang Jeongbeom , Yoon Jongwon , Ban Jonghyeon , Song Chiwon , Cho Seong J.
Published: March 2022

Biology is characterized by smooth, elastic, and nonplanar surfaces; as a consequence, soft electronics that enable interfacing with nonplanar surfaces allow applications that could not be achieved with the rigid and integrated circuits that exist today. Here, we review the latest examples of technologies and methods that can replace elasticity through a structural approach; these approaches can modify mechanical properties, thereby improving performance, while maintaining the existing material integrity. Furthermore, an overview of the recent progress in wave/wrinkle, stretchable interconnect, origami/kirigami, crack, nano/micro, and textile structures is provided. Finally, potential applications and expected developments in soft electronics are discussed.
Toward Mechanically Robust Crosslinked Elastomers through Phase Transfer Agent Tuning the Solubility of Zn2+ in the Organic Phase
Authors: Liu Shuang , Quan Xin-Yao , Wang Hao-Ran , Liao Shuangquan , Luo Ming-Chao
Published: March 2022

Zinc oxide (ZnO), which is toxic to aquatic organisms, is widely used as an activator in the rubber industry. The reduction of ZnO content is one of the efficient ways to tackle ecological environment impacts induced by ZnO. However, the incompatibility between Zn2+ and organic matrix inhibits the solubility and activity of Zn2+ in the organic matrix, causing the heavy use of ZnO. This work develops a phase transfer agent with Zn2+-philic structure and oleophilic structure to increase the solubility of Zn2+ in the organic matrix. The phase transfer agent and Zn2+ form coordination interactions, while the hydrophobic chains of phase transfer agent and organic matrix form hydrophobic interactions. The above two interactions improve the solubility and activity of Zn2+ in the organic matrix, contributing to the formation of crosslinking network. Through the phase transfer agent strategy, we obtain the mechanically robust elastomers, and the samples with low ZnO content still maintain the superior properties. This work provides an efficient way to reduce ZnO content without sacrificing the performance of elastomers.
Detecting Micro- and Nanoplastics Released from Food Packaging: Challenges and Analytical Strategies
Authors: Cella Claudia , La Spina Rita , Mehn Dora , Fumagalli Francesco , Ceccone Giacomo , Valsesia Andrea , Gilliland Douglas
Published: March 2022

Micro- and nanoplastic (pMP and pNP, respectively) release is an emerging issue since these particles constitute a ubiquitous and growing pollutant, which not only threatens the environment but may have potential consequences for human health. In particular, there is concern about the release of secondary pMP and pNP from the degradation of plastic consumer products. The phenomenon is well-documented in relation to plastic waste in the environment but, more recently, reports of pMP generated even during the normal use of plastic food contact materials, such as water bottles, tea bags, and containers, have been published. So far, a validated and harmonized strategy to tackle the issue is not available. In this study, we demonstrate that plastic breakdown to pMP and pNP can occur during the normal use of polyethylene (PE) rice cooking bags and ice-cube bags as well as of nylon teabags. A multi-instrumental approach based on Raman microscopy, X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and particular attention on the importance of sample preparation were applied to evaluate the chemical nature of the released material and their morphology. In addition, a simple method based on Fourier transform infrared (FT-IR) spectroscopy is proposed for pNP mass quantification, resulting in the release of 1.13 ± 0.07 mg of nylon 6 from each teabag. However, temperature was shown to have a strong impact on the morphology and aggregation status of the released materials, posing to scientists and legislators a challenging question: are they micro- or nanoplastics or something else altogether?
Improvement of Anchorage Performance of Carbon Fiber-Reinforced Polymer Cables
Authors: Kim Tae-Kyun , Jung Woo-Tai
Published: March 2022

Prestressed concrete composed of steel materials is increasingly used in various social infrastructures, such as bridges (cables), nuclear containment structures, liquefied natural gas (LNG) tanks, and structural reinforcements. This study aimed to substitute the steel in bridge cables with fiber-reinforced polymers (FRPs) to prevent the damage caused by the performance degradation of corroded prestressed steel. An optimized single-anchorage system was derived by applying multiple variables, such as the surface treatment, number of insert layers, and sleeve processing companies, to improve the maximum load and bonding with the anchorage system sleeve using the carbon FRP (CFRP) cable. The B-L-4 specimen (sleeve specifications of company B, longitudinal surface treatment, and four insert layers) was determined to be the optimized single-anchorage system. When the tensile test was conducted after applying the optimized single-anchorage system to the three- and seven-multi-anchorage systems, the tensile performances of B-L-4 were 100 and 95% of the one-multi-anchorage system, respectively. Considering that the problems associated with the construction of three- and seven-multi-anchorage systems have been addressed, these systems can be applied to actual bridges in the future, and can significantly benefit their maintenance.
Grafting of Thiazole Derivative on Chitosan Magnetite Nanoparticles for Cadmium Removal—Application for Groundwater Treatment
Authors: Hamza Mohammed F. , Abdel-Rahman Adel A.-H. , Negm Alyaa S. , Hamad Doaa M. , Khalafalla Mahmoud S. , Fouda Amr , Wei Yuezhou , Amer Hamada H. , Alotaibi Saad H. , Goda Adel E.-S.
Published: March 2022

The synthesis and developments of magnetic chitosan nanoparticles for high efficiency removal of the cadmium ions from aquatic medium are one of the most challenging techniques. Highly adsorptive composite (MCH-ATA) was produced by the reaction of chitosan with formaldehyde and amino thiazole derivative. The sorbent was characterized by FTIR, elemental analyses (EA), SEM-EDX, TEM analysis, TGA and titration (volumetric). The modified material includes high nitrogen and sulfur contents (i.e., 4.64 and 1.35 mmol g−1, respectively), compared to the pristine material (3.5 and 0 mmol g−1, respectively). The sorption was investigated for the removal of Cd(II) ions from synthetic (prepared) solution before being tested towards naturally contaminated groundwater in an industrial area. The functionalized sorbent shows a high loading capacity (1.78 mmol Cd g−1; 200 mg Cd g−1) compared to the pristine material (0.61 mmol Cd g−1; 68.57 mg Cd g−1), while removal of about 98% of Cd with capacity (6.4 mg Cd g−1) from polymetallic contaminated groundwater. The sorbent displays fast sorption kinetics compared to the non-modified composite (MCH); 30 min is sufficient for complete sorption for MCH-ATA, while 60–90 min for the MCH. PFORE fits sorption kinetics for both sorbents, whereas the Langmuir equation fits for MCH and Langmuir and Sips for MCH-ATA for sorption isotherms. The TEM analysis confirms the nano scale size, which limits the diffusion to intraparticle sorption properties. The 0.2 M HCl solution is a successful desorbing agent for the metal ions. The sorbent was applied for the removal of cadmium ions from the contaminated underground water and appears to be a promising process for metal decontamination and water treatment.
Modulating Role of Co-Solutes in Complexation between Bovine Serum Albumin and Sodium Polystyrene Sulfonate
Authors: Simončič Matjaž , Lukšič Miha
Published: March 2022

The action of three types of co-solutes: (i) salts (NaCl, NaBr, NaI), (ii) polymer (polyethylene glycol; PEG-400, PEG-3000, PEG-20000), and (iii) sugars (sucrose, sucralose) on the complexation between bovine serum albumin (BSA) and sodium polystyrene sulfonate (NaPSS) was studied. Three critical pH parameters were extracted from the pH dependence of the solution’s turbidity: pHc corresponding to the formation of the soluble complexes, pHΦ corresponding to the formation of the insoluble complexes, and pHopt corresponding to the charge neutralization of the complexes. In the presence of salts, the formation of soluble and insoluble complexes as well as the charge neutralization of complexes was hindered, which is a consequence of the electrostatic screening of attractive interactions between BSA and NaPSS. Distinct anion-specific trends were observed in which the stabilizing effect of the salt increased in the order: NaCl < NaBr < NaI. The presence of PEG, regardless of its molecular weight, showed no measurable effect on the formation of soluble complexes. PEG-400 and PEG-3000 showed no effect on the formation of insoluble complexes, but PEG-20000 in high concentrations promoted their formation due to the molecular crowding effect. The presence of sugar molecules had little effect on BSA-NaPSS complexation. Sucralose showed a minor stabilizing effect with respect to the onset of complex formation, which was due to its propensity to the protein surface. This was confirmed by the fluorescence quenching assay (Stern-Volmer relationship) and all-atom MD simulations. This study highlights that when evaluating the modulatory effect of co-solutes on protein-polyelectrolyte interactions, (co-solute)-protein interactions and their subsequent impact on protein aggregation must also be considered.
Assessment of the Influence of Size and Concentration on the Ecotoxicity of Microplastics to Microalgae Scenedesmus sp., Bacterium Pseudomonas putida and Yeast Saccharomyces cerevisiae
Authors: Miloloža Martina , Bule Kristina , Prevarić Viktorija , Cvetnić Matija , Ukić Šime , Bolanča Tomislav , Kučić Grgić Dajana
Published: March 2022

The harmful effects of microplastics are not yet fully revealed. This study tested harmful effects of polyethylene (PE), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) microplastics were tested. Growth inhibition tests were conducted using three microorganisms with different characteristics: Scenedesmus sp., Pseudomonas putida, and Saccharomyces cerevisiae. The growth inhibition test with Scenedesmus sp. is relatively widely used, while the tests with Pseudomonas putida and Saccharomyces cerevisiae were, to our knowledge, applied to microplastics for the first time. The influence of concentration and size of microplastic particles, in the range of 50–1000 mg/L and 200–600 µm, was tested. Determined inhibitions on all three microorganisms confirmed the hazardous potential of the microplastics used. Modeling of the inhibition surface showed the increase in harmfulness with increasing concentration of the microplastics. Particle size showed no effect for Scenedesmus with PE, PP and PET, Pseudomonas putida with PS, and Saccharomyces cerevisiae with PP. In the remaining cases, higher inhibitions followed a decrease in particle size. The exception was Scenedesmus sp. with PS, where the lowest inhibitions were obtained at 400 µm. Finally, among the applied tests, the test with Saccharomyces cerevisiae proved to be the most sensitive to microplastics.
Light-Activated Elongation/Shortening and Twisting of a Nematic Elastomer Balloon
Authors: Zhou Lin , Wang Yujie , Li Kai
Published: March 2022

Nematic elastomer balloons with inflation-induced axial contraction and shear/torsion effect can be used as actuators for soft robots, artificial muscles, and biomedical instruments. The nematic elastomer can also generate drastic shape changes under illumination, and thus light can be utilized to activate the deformation of nematic elastomer balloons with huge advantages of being accurate, fast, untethered, and environmentally sustainable without chemical byproducts. To explore light-activated deformation behaviors of the balloon, a phenomenological relationship between light intensity and material parameters describing polymer backbone anisotropy is proposed from experiments, and a theoretical model of an optically-responsive nematic elastomer balloon is established based on the nematic elastomer theory. Various light-activated elongation/shortening and twisting behaviors in the cases of free-standing and axial-loading are presented and their mechanisms are elucidated. The light intensity and initial mesogen angle have great influences on the light-activated deformations including the radius, length, shearing angle and mesogen angle. Light can be easily controlled to trigger rich deformation processes, including elongation/shortening and torsion. The results of this paper are expected to promote the understanding of the light-activated deformation behaviors of the nematic elastomer balloon, and the applications in light-activated actuators and machines.
Tung Oil Thermal Treatment Improves the Visual Effects of Moso Bamboo Materials
Authors: Tang Tong , Fei Benhua , Song Wei , Su Na , Sun Fengbo
Published: March 2022

Color is one of the most important characteristics of a material’s appearance, which affects the additional value of bamboo and psychological feelings of users. Previous studies have shown that the dimensional stability, mildew resistance and durability of bamboo were improved after tung oil thermal treatment. In this study, the effects of tung oil thermal treatment on bamboo color at different temperatures and durations of time were investigated. The results show that the lightness (L*) of bamboo decreased as the tung oil temperature or duration of time increased. The red–green coordinates (a*) and color saturation (C*) of bamboo were gradually increased as the tung oil temperature rose from 23 °C to 160 °C, while the a* and C* were gradually decreased when the temperature continued to rise from 160 °C to 200 °C. There was no significant difference in the yellow–blue coordinates (b*) of bamboo when the duration was prolonged from 0.5 h to 3 h with tung oil thermal treatment at 140 °C. Eye movement data show that the popularity of bamboo furniture was significantly improved at 23–100 °C and slightly improved at 160–180 °C with tung oil treatment. Therefore, tung oil thermal treatment plays a positive role in improving visual effects and additional value of bamboo.
Fabrication and Property Characterization of Long-Glass-Fiber-Reinforced Polypropylene Composites Processed Using a Three-Barrel Injection Molding Machine
Authors: Liou Guan-Yan , Su Chi-Wei , Huang Po-Wei , Hwang Sheng-Jye , Huang Chao-Tsai , Peng Hsin-Shu
Published: March 2022

Processing equipment and parameters will highly influence the properties of long-fiber-reinforced injection-molded thermoplastic composites, leading to different fiber lengths and orientations. Thus, maintaining fiber length during the injection molding process is always a big challenge for engineers. This study uses long-glass-fiber-reinforced polypropylene with 25 mm fiber length and a special-built novel injection molding machine with a three-barrel injection unit, including a plasticizing screw, an injection plunger, and a packing plunger, to fabricate injection molding parts while retaining long fiber length. This study also discusses the influence of process parameters, such as back pressure, screw speed, melt temperature, and different flow paths, on the properties of long-glass-fiber-reinforced composites. The experiment results show that a higher screw speed and back pressure will reduce the fiber length in the injection-molded parts. However, using appropriate parameter settings can maintain the fiber length to more than 10 mm. It was found that by increasing the back pressure, the cross direction of the fiber orientation can be increased by up to 15% and the air trap volume fraction can be decreased by up to 86%. Setting appropriate back pressure under a low screw speed will increase the tensile strength. Finally, it was found that the single-edge-gate path results in a higher tensile strength than that of the single-sprue-gate path due to the retainment of longer fiber length in the injection-molded part.
Characteristic and Synthesis of High-Temperature Resistant Liquid Crystal Epoxy Resin Containing Boron Nitride Composite
Authors: Wu Li-Chuan , Huang Yi-Wen , Yeh Yao-Ming , Lin Chih-Hung
Published: March 2022

Five liquid crystal epoxy resins and composites containing flat boron nitride (f-BN) and spherical boron nitride (s-BN) were successfully synthesized. The chemical structures, crystal diffraction, and thermal conductivity of the liquid crystal (LC) epoxy composites were measured using Nuclear Magnetic Resonance (NMR), Differential Scanning Calorimetry (DSC), X-ray, and Discovery Xenon Flash. In this study, the molecular arrangement of five LC epoxy resins and the thermal conductivity of their composites were carefully discussed. Several different amounts of flat boron nitride and spherical boron nitride were added to the five LC epoxy resins. The influence of nano-scale ceramic materials, f-BN, and s-BN, on the thermal conductivity of the LC epoxy resins, was studied. It is worth noting that the thermal conductivity of the spherical boron nitride composite demonstrated a better result than that of the flat boron nitride composite. In simpler terms, the thermal conductivity of the composites is closely related to the molecular arrangement of the LC resin and the amount of BN added. The results demonstrate that the SBPDAE/s-BN (60%) composite shows the highest thermal conductivity of 9.36 W/mK in the vertical direction. These data prove that the LC alignment of the matrix will greatly enhance the thermal conductivity of the composites.
Modification of Hot-Melt Adhesives Based on Metallocene Poly(ethylene-propylene) Copolymer for High Adhesion to Polar Surfaces
Authors: Novák Igor , Preto Jozef , Vanko Vladimír , Rychlý Jozef , Pavlinec Juraj , Chodák Ivan
Published: March 2022

A procedure is described of grafting the acrylic acid onto an oxygen/ozone-activated metallocene poly(ethylene-co-propylene). Consequently, the grafted copolymer is applied as a component in a metallocene polyolefin-based hot-melt adhesive composition with increased adhesion. The surface properties and adhesion strength of the prepared hot-melt adhesive (HMA) were determined and used to account for the effect of grafting. The application of grafted polyolefin as one of the components of the HMA mixture provides significant increase in adhesive strength, and it also results in increased compatibility and negligible effects on the technological parameters of the final composition. The obtained results may have significant impact for the practical application of prepared HMA for book bonding.
Critical Visual Religion Approach: When Ethnographic Filmmaking Blends with the Critical Approach to Religion, a Japanese Case Study
Authors: Vecchi Ilaria
Published: March 2022

This article draws on the research and practice developed during my doctorate and fieldwork in Japan. In this work, I consider the implication of using the critical religion approach and the visual ethnographic methodology for critically investigating what is commonly labelled as religion and its representation as observed in Japan with particular reference to my fieldwork in Tohoku. I begin by reviewing the concept of religion in Japan, in particular the character of the idea and the use of the critical religion approach. I continue with an analysis of ethnographic filmmaking, focusing on cases that inspired my visual ethnographic filmic approach. I discuss how the two methods informed each other, creating a visual ethnographic technique founded on the critical religion approach as well as sensory, participatory and creative ethnographic filmmaking methods I developed and applied to my documentary, Tohoku Monogatari—A Story from the Northeast of Japan. With this article, I contend the necessity of a critical approach to the representation of religions which could be achieved with what I named the critical visual religion approach.
Yehudite Imaginations of King Darius and His Officials: Views from the Province beyond the River
Authors: Joachimsen Kristin
Published: March 2022

This article analyzes representations of the Persian king Darius and his officials in the Books of Haggai, Zechariah 1–8, and Ezra 4–6 in the current Hebrew Bible. These writings, produced in the Persian period or somewhat later, portray these literary characters in various ways in relation to the restoration of the community, city, and temple of YHWH in Jerusalem. In biblical scholarship, the main interest has been to scrutinize the conditions behind the textual representations of Darius, related to dating the selected texts and the temple restoration, as well as Darius’s role as the central supplier of Achaemenid imperial ideology. The current study suggests refocusing by highlighting the historical significance of the literary imaginations of this monarch. What is at stake is not the historical Darius or the officials Zerubbabel, Sheshbazzar, and Tattenai, but rather literary representations of them suiting the needs of those who produced them. In Haggai and Zechariah 1–8, Darius’s role in the temple restoration is downplayed, while in Haggai, Zerubbabel is represented by a blend of Yahwistic and imperial signs and symbols, and in Zechariah 1–8, the imperial connotations are toned down. This is while Zerubbabel is decisive for authorizing both the temple community and the prophet. In Ezra 4–6, Darius is one of many Persian kings engaged in the restoration of the temple and the city of Jerusalem. While Zerubbabel gains support from the prophets Haggai and Zechariah, Sheshbazzar brings the vessels back to Jerusalem and lays the foundations of the temple on King Cyrus’s command. At the same time, Tattenai gets Cyrus’s order confirmed and, apart from that, is asked to stay away from the works of the Yehudites. By analyzing the representations of Darius and other Persian officials through a cultural-historical lens, selection and perspectivization are stressed. The selected writings convey local negotiations of power relations with the empire in terms of keeping a position in the imperial hierarchy while, at the same time, cultivating the identity of their subaltern group through certain symbols, institutions, and practices.
Dynamics Modeling of a Delta Robot with Telescopic Rod for Torque Feedforward Control
Authors: Zhang Sai , Liu Xinjun , Yan Bingkai , Han Xiangdong , Bi Jie
Published: March 2022

This paper presents dynamics modeling of a Delta robot with three revolute legs and a telescopic rod. Firstly, two generalized coordinate systems are established to describe the relationship between the movement of the telescopic rod and the position of the moving platform, and the telescopic rod system kinematics are established through singularity analysis. Secondly, taking the telescopic rod as the research object, the corresponding dynamics model is established using the Euler–Lagrange method. Moreover, this paper proposes a method to convert the force exerted by the telescopic rod motion on the moving platform into actuator torques. Thirdly, the dynamics model of the Delta robot with a telescopic rod is established, and numerical simulations are performed to demonstrate this approach. Finally, the influence of the telescopic rod on the actuator torques is verified using an experiment. A comparison is drawn between the two dynamics models used in torque feedforward control to validate the proposed dynamics model.
Evaluation of Reasonable Stocking Rate Based on the Relative Contribution of Climate Change and Grazing Activities to the Productivity of Alpine Grasslands in Qinghai Province
Authors: Zhao Li , Liu Zhenhua , Hu Yueming , Zhou Wu , Peng Yiping , Ma Tao , Liu Luo , Li Shihua , Wang Liya , Mao Xiaoyun
Published: March 2022

An accurate assessment of the stocking rate is crucial for maintaining the stable function and the sustainable use of the alpine grassland ecosystem. A new scenario design method to evaluate the reasonable stocking rate is presented in the current work. First, climate change is quantified by potential net primary productivity (NPPp) and measured by adopting the Zhou Guangsheng model, and the NPP generated by anthropogenic activities (NPPh) is estimated by the distinction between NPPp and actual NPP (NPPa) calculated with the application of the Carnegie–Ames–Stanford Approach (CASA) model. Second, using the NPPh and actual grassland productivity consumed by livestock (NPPac), the reasonable stocking rate is obtained. Finally, the driving factors of NPP change in alpine grassland and the reasonable stocking rate are clarified in Qinghai Province during 2005–2018. The results reveal that the temperature of alpine grassland in Qinghai Province has a slight upward trend from 2005 to 2018, and precipitation displays a downward trend. The overall NPPp of alpine grassland demonstrated a downward trend, and precipitation is regarded as the major influencing factor. In addition, the overall NPPh of alpine grassland exhibited a downward trend. The NPPa demonstrated an overall upward trend, where 58.32% of the regional NPPa is in a state of growth, and 41.68% of the regional NPPa is in a state of degradation. According to contribution analysis, anthropogenic activities provided the primary driving factor to promote the restoration of alpine grassland in Qinghai Province. Moreover, the stocking rate must be reduced in 60.77% of the alpine grasslands in Qinghai Province, mostly situated in the eastern and southwestern parts of Qinghai Province, and the other areas must not increase future stocking rates. The current study can theoretically and technically support the construction of Qinghai as the green organic agricultural and livestock product demonstration province and the creation of an ecological civilization highland.
Detection of Direct Sun Glare on Drivers from Point Clouds
Authors: González-Collazo Silvia María , del Río-Barral Pablo , Balado Jesús , González Elena
Published: March 2022

Sunlight conditions can reduce drivers’ visibility, which is a safety concern on road networks. This research introduces a method to study sun glare incidence in road environments. Sun glare areas during daylight hours are automatically detected from mobile laser scanning (MLS) and aerial laser scanning (ALS) point clouds. The method comprises the following steps. First, the Sun’s position (solar altitude and azimuth) referring to a location is calculated. Second, the incidence of sun glare with the user’s angle of vision is analyzed based on human vision. Third, sun ray intersections with near obstacles (vegetation, building, etc.) are calculated utilizing MLS point clouds. Finally, intersections with distant obstacles (mountains) are calculated utilizing ALS point clouds. MLS and ALS data are processed in order to combine both data types, remove outliers, and optimize computational time for intersection searches (point density reduction and Delaunay triangulation). The method was tested on two real case studies, covering roads with different bearings, slopes, and surroundings. The combination of MLS and ALS data, together with the solar geometry, identify areas of risk for the visibility of drivers. Consequently, the proposed method can be utilized to reduce sun glare, implementing warnings in navigation systems.
Advancing the Solar Radiation Pressure Model for BeiDou-3 IGSO Satellites
Authors: Xia Fengyu , Ye Shirong , Chen Dezhong , Tang Longjiang , Wang Chen , Ge Maorong , Neitzel Frank
Published: March 2022

In the absence of detailed surface information, empirical solar radiation pressure (SRP) models, such as the five-parameter Empirical CODE Orbit Model (ECOM1) and its extended version-ECOM2, are widely used for modeling SRP forces acting on GNSS satellites. This study shows that the orbits of BeiDou-3 Inclined Geosynchronous Orbit satellites (IGSOs) determined with the ECOM1 model suffer from systematic once-per-revolution radial orbit errors, which can be partly reduced by the ECOM2 model. To eliminate such orbit errors, the BeiDou-3 IGSO optical coefficients are solved by using an adjustable box-wing (ABW) model and then introduced into an a priori box-wing SRP model to enhance the ECOM1 model (ECOM1 + BW). In the ABW solution, in addition to satellite body and solar panels, the contributions of the communication payloads installed on BeiDou-3 IGSO ±X panels on the SRP are also considered, which markedly improves the stability of the optical coefficient estimates. The efficiency of the developed a priori box-wing model is demonstrated through eliminated once-per-revolution radial orbit errors and decreased day boundary discontinuities. However, the orbit solutions still show significant degradations during eclipse seasons. The results of the first yaw-attitude analysis for eclipsing BeiDou-3 IGSOs show that their yaw behaviors are the same as those of BeiDou-3 CAST (China Academy of Space Technology) MEOs (Medium Earth Orbit satellites), and have been well considered in the study. This rules out the possibility that attitude errors are the potential reason for the orbit deterioration. By introducing a once-per-revolution sine term in the Sun direction (Ds term) and keeping Ds active during the Earth’s shadow transitions to the ECOM1 + BW model, the orbit performance inside the eclipse seasons is significantly improved and can be comparable to that outside the eclipse seasons.
A Decrease in the Daily Maximum Temperature during Global Warming Hiatus Causes a Delay in Spring Phenology in the China–DPRK–Russia Cross-Border Area
Authors: Su Minshu , Huang Xiao , Xu Zhen , Zhu Weihong , Lin Zhehao
Published: March 2022

Spring phenology is the most sensitive indicator of climate change and exploring its response to climate change has important implications for ecosystem processes in the study area. The temperature changes before and after the global warming hiatus may affect the spatiotemporal pattern of land surface phenology. In this paper, taking the China–DPRK (Democratic People’s Republic of Korea)–Russia cross-border region as an example, based on GIMMS NDVI data, the Polyfit-Maximum method was used to extract the start date of the vegetation growing season (SOS). The variation trend of SOS and its response to climate change were analyzed in the early (1982–1998) and late (1998–2015) periods of the warming hiatus. At the regional scale, the spatial distribution of the SOS in the China–DPRK–Russia (CDR) cross-border area presents an elevation gradient, which is earlier in high-elevation areas and later in low-elevation areas. The temporal and spatial trend of SOS is mainly correlated by daytime maximum temperature (Tmax). The significant increase in Tmax in the early period promoted the advance of SOS (0.47 days/year), and the decrease in Tmax in the later period caused the delay of SOS (0.51 days/year). While the main influencing factor of the SOS changes in the region in the early and late periods was Tmax, the response of the SOS changes in China, DPRK and Russia to climate change also changed with the dramatic temperature changes during the warming hiatus. The Chinese side is increasingly responding to Tmax, while the North Korean side is becoming less responsive to climatic factors, and precipitation and radiation on the Russian side are driving the advance of the SOS.
A Collaborative Despeckling Method for SAR Images Based on Texture Classification
Authors: Wang Gongtang , Bo Fuyu , Chen Xue , Lu Wenfeng , Hu Shaohai , Fang Jing
Published: March 2022

Speckle is an unavoidable noise-like phenomenon in Synthetic Aperture Radar (SAR) imaging. In order to remove speckle, many despeckling methods have been proposed during the past three decades, including spatial-based methods, transform domain-based methods, and non-local filtering methods. However, SAR images usually contain many different types of regions, including homogeneous and heterogeneous regions. Some filters could despeckle effectively in homogeneous regions but could not preserve structures in heterogeneous regions. Some filters preserve structures well but do not suppress speckle effectively. Following this theory, we design a combination of two state-of-the-art despeckling tools that can overcome their respective shortcomings. In order to select the best filter output for each area in the image, the clustering and Gray Level Co-Occurrence Matrices (GLCM) are used for image classification and weighting, respectively. Clustering and GLCM use the co-registered optical images of SAR images because their structure information is consistent, and the optical images are much cleaner than SAR images. The experimental results on synthetic and real-world SAR images show that our proposed method can provide a better objective performance index under a strong noise level. Subjective visual inspection demonstrates that the proposed method has great potential in preserving structural details and suppressing speckle noise.
A Machine Learning Snowfall Retrieval Algorithm for ATMS
Authors: Sanò Paolo , Casella Daniele , Camplani Andrea , D’Adderio Leo Pio , Panegrossi Giulia
Published: March 2022

This article describes the development of a machine learning (ML)-based algorithm for snowfall retrieval (Snow retrievaL ALgorithm fOr gpM–Cross Track, SLALOM-CT), exploiting ATMS radiometer measurements and using the CloudSat CPR snowfall products as references. During a preliminary analysis, different ML techniques (tree-based algorithms, shallow and convolutional neural networks—NNs) were intercompared. A large dataset (three years) of coincident observations from CPR and ATMS was used for training and testing the different techniques. The SLALOM-CT algorithm is based on four independent modules for the detection of snowfall and supercooled droplets, and for the estimation of snow water path and snowfall rate. Each module was designed by choosing the best-performing ML approach through model selection and optimization. While a convolutional NN was the most accurate for the snowfall detection module, a shallow NN was selected for all other modules. SLALOM-CT showed a high degree of consistency with CPR. Moreover, the results were almost independent of the background surface categorization and the observation angle. The reliability of the SLALOM-CT estimates was also highlighted by the good results obtained from a direct comparison with a reference algorithm (GPROF).
Combining Sample Plot Stratification and Machine Learning Algorithms to Improve Forest Aboveground Carbon Density Estimation in Northeast China Using Airborne LiDAR Data
Authors: Chen Mingjie , Qiu Xincai , Zeng Weisheng , Peng Daoli
Published: March 2022

Timely, accurate estimates of forest aboveground carbon density (AGC) are essential for understanding the global carbon cycle and providing crucial reference information for climate-change-related policies. To date, airborne LiDAR has been considered as the most precise remote-sensing-based technology for forest AGC estimation, but it suffers great challenges from various uncertainty sources. Stratified estimation has the potential to reduce the uncertainty and improve the forest AGC estimation. However, the impact of stratification and how to effectively combine stratification and modeling algorithms have not been fully investigated in forest AGC estimation. In this study, we performed a comparative analysis of different stratification approaches (non-stratification, forest type stratification (FTS) and dominant species stratification (DSS)) and different modeling algorithms (stepwise regression, random forest (RF), Cubist, extreme gradient boosting (XGBoost) and categorical boosting (CatBoost)) to identify the optimal stratification approach and modeling algorithm for forest AGC estimation, using airborne LiDAR data. The analysis of variance (ANOVA) was used to quantify and determine the factors that had a significant effect on the estimation accuracy. The results revealed the superiority of stratified estimation models over the unstratified ones, with higher estimation accuracy achieved by the DSS models. Moreover, this improvement was more significant in coniferous species than broadleaf species. The ML algorithms outperformed stepwise regression and the CatBoost models based on DSS provided the highest estimation accuracy (R2 = 0.8232, RMSE = 5.2421, RRMSE = 20.5680, MAE = 4.0169 and Bias = 0.4493). The ANOVA of the prediction error indicated that the stratification method was a more important factor than the regression algorithm in forest AGC estimation. This study demonstrated the positive effect of stratification and how the combination of DSS and the CatBoost algorithm can effectively improve the estimation accuracy of forest AGC. Integrating this strategy with national forest inventory could help improve the monitoring of forest carbon stock over large areas.
Multi-Output Network Combining GNN and CNN for Remote Sensing Scene Classification
Authors: Peng Feifei , Lu Wei , Tan Wenxia , Qi Kunlun , Zhang Xiaokang , Zhu Quansheng
Published: March 2022

Scene classification is an active research area in the remote sensing (RS) domain. Some categories of RS scenes, such as medium residential and dense residential scenes, would contain the same type of geographical objects but have various spatial distributions among these objects. The adjacency and disjointness relationships among geographical objects are normally neglected by existing RS scene classification methods using convolutional neural networks (CNNs). In this study, a multi-output network (MopNet) combining a graph neural network (GNN) and a CNN is proposed for RS scene classification with a joint loss. In a candidate RS image for scene classification, superpixel regions are constructed through image segmentation and are represented as graph nodes, while graph edges between nodes are created according to the spatial adjacency among corresponding superpixel regions. A training strategy of a jointly learning CNN and GNN is adopted in the MopNet. Through the message propagation mechanism of MopNet, spatial and topological relationships imbedded in the edges of graphs are employed. The parameters of the CNN and GNN in MopNet are updated simultaneously with the guidance of a joint loss via the backpropagation mechanism. Experimental results on the OPTIMAL-31 and aerial image dataset (AID) datasets show that the proposed MopNet combining a graph convolutional network (GCN) or graph attention network (GAT) and ResNet50 achieves state-of-the-art accuracy. The overall accuracy obtained on OPTIMAL-31 is 96.06% and those on AID are 95.53% and 97.11% under training ratios of 20% and 50%, respectively. Spatial and topological relationships imbedded in RS images are helpful for improving the performance of scene classification.
Classification of Geomorphic Units and Their Relevance for Nutrient Retention or Export of a Large Lowland Padma River, Bangladesh: A NDVI Based Approach
Authors: Gani Md Ataul , Kwast Johannes van der , McClain Michael E. , Gettel Gretchen , Irvine Kenneth
Published: March 2022

Geomorphic classification of large rivers identifies morphological patterns, as a foundation for estimating biogeochemical and ecological processes. In order to support the modelling of in-channel nutrient retention or export, the classification of geomorphic units (GUs) was done in the Padma River, Bangladesh, a large and geomorphically-complex lowland river. GUs were classified using the normalized difference vegetation index (NDVI) four times over a year, so as to cover the seasonal variation of water flows. GUs were categorized as primary and secondary channels (C & S); longitudinal bar (L); transverse bar (T); side bar (SB); unvegetated bank (EK); dry channel (ED); island (VI); and water depression (WD). All types of GUs were observed over the four distinct annual seasons, except ED, which was absent during the high flow, monsoon season. Seasonal variation of the surface area of GUs and discharge showed an inverse relation between discharge and exposed surface areas of VI, L, T, and SB. Nutrients mainly enter the river system through water and sediments, and during monsoon, the maximum portion of emergent GUs were submerged. Based on the assumption that nutrient retention is enhanced in the seasonally inundated portions of GUs, nutrient retention-/export-relevant geomorphic units (NREGUs) were identified. Seasonal variation in the area of NREGUs was similar to that of GUs. The mean NDVI values of the main identified NREGUs were different. The variation of NDVI values among seasons in these NREGUs resulted from changes of vegetation cover and type. The variation also occurred due to alteration of the surface area of GUs in different seasons. The changes of vegetation cover indicated by NDVI values across seasons are likely important drivers for biogeochemical and ecological processes.
Proximal Remote Sensing-Based Vegetation Indices for Monitoring Mango Tree Stem Sap Flux Density
Authors: Jin Jia , Huang Ning , Huang Yuqing , Yan Yan , Zhao Xin , Wu Mengjuan
Published: March 2022

Plant water use is an important function reflecting vegetation physiological status and affects plant growth, productivity, and crop/fruit quality. Although hyperspectral vegetation indices have recently been proposed to assess plant water use, limited sample sizes for established models greatly astricts their wide applications. In this study, we have managed to gather a large volume of continuous measurements of canopy spectra through proximally set spectroradiometers over the canopy, enabling us to investigate the feasibility of using continuous narrow-band indices to trace canopy-scale water use indicated by the stem sap flux density measured with sap flow sensors. The results proved that the newly developed D (520, 560) index was optimal to capture the variation of sap flux density under clear sky conditions (R2 = 0.53), while the best index identified for non-clear sky conditions was the D (530, 575) (R2 = 0.32). Furthermore, the bands used in these indices agreed with the reported sensitive bands for estimating leaf stomatal conductance which has a critical role in transpiration rate regulation over a short time period. Our results should point a way towards using proximal hyperspectral indices to trace tree water use directly.
Manifold-Based Multi-Deep Belief Network for Feature Extraction of Hyperspectral Image
Authors: Li Zhengying , Huang Hong , Zhang Zhen , Shi Guangyao
Published: March 2022

Deep belief networks (DBNs) have been widely applied in hyperspectral imagery (HSI) processing. However, the original DBN model fails to explore the prior knowledge of training samples which limits the discriminant capability of extracted features for classification. In this paper, we proposed a new deep learning method, termed manifold-based multi-DBN (MMDBN), to obtain deep manifold features of HSI. MMDBN designed a hierarchical initialization method that initializes the network by local geometric structure hidden in data. On this basis, a multi-DBN structure is built to learn deep features in each land-cover class, and it was used as the front-end of the whole model. Then, a discrimination manifold layer is developed to improve the discriminability of extracted deep features. To discover the manifold structure contained in HSI, an intrinsic graph and a penalty graph are constructed in this layer by using label information of training samples. After that, the deep manifold features can be obtained for classification. MMDBN not only effectively extracts the deep features from each class in HSI, but also maximizes the margins between different manifolds in low-dimensional embedding space. Experimental results on Indian Pines, Salinas, and Botswana datasets reach 78.25%, 90.48%, and 97.35% indicating that MMDBN possesses better classification performance by comparing with some state-of-the-art methods.
Deriving Nutrient Concentrations from Sentinel-3 OLCI Data in North-Eastern Baltic Sea
Authors: Soomets Tuuli , Toming Kaire , Jefimova Jekaterina , Jaanus Andres , Põllumäe Arno , Kutser Tiit
Published: March 2022

Nutrients are important elements in marine ecosystems and water quality, and have a major role in the eutrophication of water bodies. Monitoring nutrient loads is especially important for the Baltic Sea, which is especially sensitive to the eutrophication. Using optical remote sensing data in mapping total nitrogen (TN) and total phosphorus (TP) is challenging because these substances do not have a direct influence on the water optics that remote sensing sensors can detect. On the other hand, it would be very rewarding. In this study, more than 25,000 Sentinel-3 Ocean and Land Colour Instrument (OLCI) data algorithms were tested in order to detect the TN and TP concentrations in the Estonian marine waters between 2016–2021. The TN estimations were well derived for Estonian marine waters (R2 = 0.73, RMSE = 4.87 µmolN L−1, MAPE = 14%, n = 708), while the TP estimations were weaker (R2 = 0.38, RMSE = 0.23 µmolP L−1, MAPE = 24%, n = 730). The Estonian marine waters were divided into six geographic regions in order to study the effect of regional water quality on the TN and TP retrievals. The nutrient concentrations were derived in every region when spring and summer periods were treated separately. In this study, the detection of both nutrients was more successful in more closed areas with P deficiency, while in open sea areas it was more challenging. This study shows that it is possible to estimate nutrients, especially TN, from remote sensing data. Consequently, remote sensing could provide a reliable support to the conventional monitoring by covering large marine areas with high temporal and spatial resolution data.
Distributed Feedback Interband Cascade Laser Based Laser Heterodyne Radiometer for Column Density of HDO and CH4 Measurements at Dunhuang, Northwest of China
Authors: Lu Xingji , Huang Yinbo , Wu Pengfei , Liu Dandan , Ma Hongliang , Wang Guishi , Cao Zhensong
Published: March 2022

Remote sensing of HDO and CH4 could provide valuable information on environmental and climatological studies. In a recent contribution, we reported a 3.53 μm distributed feedback (DFB) inter-band cascade laser (ICL)-based heterodyne radiometer. In the present work, we present the details of measurements and inversions of HDO and CH4 at Dunhuang, Northwest of China. The instrument line shape (ILS) of laser heterodyne radiometer (LHR) is discussed firstly, and the spectral resolution is about 0.004 cm−1 theoretically according to the ILS. Furthermore, the retrieval algorithm, optimal estimation method (OEM), combined with LBLRTM (Line-by-line Radiative Transfer Model) for retrieving the densities of atmospheric HDO and CH4 are investigated. The HDO densities were retrieved to be less than 1.0 ppmv, while the CH4 densities were around 1.79 ppmv from 20 to 24 July 2018. The correlation coefficient of water vapor densities retrieved by LHR and EM27/SUN is around 0.6, the potential reasons for the differences were discussed. Finally, in order to better understand the retrieval procedure, the Jacobian value and the Averaging Kernels are also discussed.