bluuebunny/crossref_metadata_2025 huggingface dataset:
Controlled Release of Chlorogenic Acid from Polyvinyl Alcohol/Poly(γ-Glutamic Acid) Blended Electrospun Nanofiber Mats with Potential Applications in Diabetic Foot Treatment
Authors: Sandoval-Herrera Isela , Romero-García Jorge , Ledezma-Pérez Antonio , Alvarado-Canché Carmen , Torres-Lubian Román , De-León Arxel
Published: September 2021

This work biosynthesized poly(γ-glutamic acid) (γ-PGA) produced by Bacillus licheniformis ATCC-9945a. This material was utilized to prepare electrospun nanofibers with solutions of 10% polyvinyl alcohol (PVA) (w/v) mixed with γ-PGA at 5 and 10% w/v, intended as a wound dressing for diabetic foot treatment. These solutions were loaded with chlorogenic acid (CGA), an active hypoglycemic agent. Morphological analysis showed a decrease in size of the fibers with the combination of PVA/γ-PGA compared to pure PVA nanofibers, which was attributed to the hydrogen bonding interactions between the glutaraldehyde vapors, γ-PGA, and PVA that permitted nanofiber cross-linking and allowed CGA release. The in vitro release analysis showed that the PVA membranes reached 28% delivery after the first 24 h. Notably, the nanofiber mat with PVA blended with 5% γ-PGA reached 57% delivery, and the PVA nanofiber with 10% γ-PGA reached 66% release after the same amount of time. The rate constant for the release kinetics showed that PVA with 5% γ-PGA had a higher value than that of the other samples, reaching saturation first.
Influence of Curing Time on the Microbiological Behavior of Bulk-Fill Nanohybrid Resin Composites
Authors: Ionescu Andrei C. , Comba Allegra , Brambilla Eugenio , Ilie Nicoleta , Breschi Lorenzo , Cadenaro Milena , Scotti Nicola
Published: September 2021

This in vitro study aimed to evaluate the influence of curing time on surface characteristics and microbiological behavior of three bulk-fill resin-based composites (RBCs). Materials were light-cured for either 10 s or 80 s, then finished using a standard clinical procedure. They were characterized by surface morphology (SEM), surface elemental composition (EDS), surface roughness (SR), and surface free energy (SFE). Microbiological behavior was assessed as S. mutans adherence (2 h) and biofilm formation (24 h) using a continuous-flow bioreactor. Statistical analysis included a two-way ANOVA and Tukey’s test (p < 0.05). Materials differed substantially as filler shape, dimension, elemental composition and resin matrix composition. Significant differences between materials were found for SR, SFE, and microbiological behavior. Such differences were less pronounced or disappeared after prolonged photocuring. The latter yielded significantly lower adherence and biofilm formation on all tested materials, similar to conventional RBCs. Improved photoinitiators and UDMA-based resin matrix composition may explain these results. No correlation between surface characteristics and microbiological behavior can explain the similar microbiological behavior of bulk-fill materials after prolonged photocuring. This different performance of bulk-fill materials compared with conventional RBCs, where surface characteristics, especially surface chemistry, influence microbiological behavior, may have important implications for secondary caries occurrence and restoration longevity.
Constitutive Modelling of Polylactic Acid at Large Deformation Using Multiaxial Strains
Authors: Sweeney John , Spencer Paul , Thompson Glen , Barker David , Coates Phil
Published: September 2021

Sheet specimens of a PLLA-based polymer have been extended at a temperature near to the glass transition in both uniaxial and planar tension, with stress relaxation observed for some time after reaching the final strain. Both axial and transverse stresses were recorded in the planar experiments. In all cases during loading, yielding at small strain was followed by a drop in true stress and then strain hardening. This was followed by stress relaxation at constant strain, during which stress dropped to reach an effectively constant level. Stresses were modelled as steady state and transient components. Steady-state components were identified with the long-term stress in stress relaxation and associated with an elastic component of the model. Transient stresses were modelled using Eyring mechanisms. The greater part of the stress during strain hardening was associated with dissipative Eyring processes. The model was successful in predicting stresses in both uniaxial and planar extension over a limited range of strain rate.
Effects of Vapor Pressure of Desiccant Solution on Mass Transfer Performance for a Spray-Bed Absorber
Authors: Wu Hung-Ta , Chung Chin-Chun
Published: September 2021

The depression in vapor pressure caused by adding desiccant to liquid water can be regarded as the driving force for the dehumidification process. The vapor pressure depends on the temperature and the concentration. Therefore, the purpose in this study is to discuss the mass transfer performance affected by operating variables and to show that the vapor pressure is a key factor affecting the mass transfer performance for absorbing water vapor by triethylene glycol (TEG) solution. The experimental results showed that the mass transfer coefficients were decreased with increases in the temperature and increased with increases in the concentration, respectively, while the mass transfer coefficients were increased with increases in the vapor pressure depression. Although both the average error is within 5% among the mass transfer correlation involving the vapor pressure and that involving the temperature and the concentration in predicting the mass transfer coefficient, there are just two terms, those are vapor pressure and fluid flow rate, associated with operating variables used in the mass transfer correlation. The depression in vapor pressure was not only proved to be the driving force for absorbing water vapor by a desiccant solution, but also a key factor affecting the mass transfer performance.
Challenges towards Targeted Drug Delivery in Cancer Nanomedicines
Authors: Hafeez Muhammad Nadeem , Celia Christian , Petrikaite Vilma
Published: September 2021

Despite cancer nanomedicine celebrates already thirty years since its introduction, together with the achievements and progress in cancer treatment area, it still undergoes serious disadvantages that must be addressed. Since the first observation that macromolecules tend to accumulate in tumor tissue due to fenestrated endothelial of vasculature, considered as the “royal gate” in drug delivery field, more than dozens of nanoformulations have been approved and introduced into the practice for cancer treatment. Lipid, polymeric, and hybrid nanocarriers are biocompatible nano-drug delivery systems (NDDs) having suitable physicochemical properties and modulate payload release in response to specific chemical or physical stimuli. Biopharmaceutical properties of NDDs and their efficacy in animal models and humans can significantly affect their impact and perspective in nanomedicine. One of the future directions could be focusing on personalized cancer treatment, considering the heterogeneity and complexity of each patient tumor tissue and the designing of multifunctional targeted NDDs combining synthetic nanomaterials and biological components, like cellular membranes, circulating proteins, RNAi/DNAi, which enforce the efficacy of NDDs and boost their therapeutic effect.
Study on Hazardous Areas of Hydrogen Fluoride Diffusion Based on CFD Simulation
Authors: Chen Siyan , Zhou Zhengqing , Ma Yong , Zhang Li , Wang Tianyi , Wang Shihao , Zhang Yinghua
Published: September 2021

Hydrogen fluoride (HF) is a typical dangerous gas in the fluorine chemical industry. Its leakage is one of the most common types of accidents in this industry, and it poses a serious threat to personnel safety and health, environmental sanitation, and social stability. In this paper, the process and consequences of an HF leakage accident in a fluorine chemical plant were simulated by using computational fluid dynamics (CFD) simulation software, and hazardous areas (lethal area, severe injury area, light injury area, and maximum allowable concentration area) of HF diffusion were determined according to the HF concentration corresponding to the degree of personal injury. Moreover, the effects of wind speed and height on hazardous areas were analyzed. The research results of this paper provide model support for similar enterprises to predict the consequences of harmful gas leakage accidents, and give suggestions on emergency evacuation and rescue work, which have practical application significance.
Modeling of Continuous PHA Production by a Hybrid Approach Based on First Principles and Machine Learning
Authors: Luna Martin F. , Ochsner Andrea M. , Amstutz Véronique , von Blarer Damian , Sokolov Michael , Arosio Paolo , Zinn Manfred
Published: September 2021

Polyhydroxyalkanoates (PHA) are renewable alternatives to traditional oil-derived polymers. PHA can be produced by different microorganisms in continuous culture under specific media composition, which makes the production process both promising and challenging. In order to achieve large productivities while maintaining high yield and efficiency, the continuous culture needs to be operated in the so-called dual nutrient limitation condition, where both the nitrogen and carbon sources are kept at very low concentrations. Mathematical models can greatly assist both design and operation of the bioprocess, but are challenged by the complexity of the system, in particular by the dual nutrient-limited growth phenomenon, where the cells undergo a metabolic shift that abruptly changes their behavior. Traditional, non-structured mechanistic models based on Monod uptake kinetics can be used to describe the bioreactor operation under specific process conditions. However, in the absence of a model description of the metabolic phenomena inside the cell, the extrapolation to a broader operation domain (e.g., different feeding concentrations and dilution rates) may present mismatches between the predictions and the actual process outcomes. Such detailed models may require almost perfect knowledge of the cell metabolism and omic-level measurements, hampering their development. On the other hand, purely data-driven models that learn correlations from experimental data do not require any prior knowledge of the process and are therefore unbiased and flexible. However, many more data are required for their development and their extrapolation ability is limited to conditions that are similar to the ones used for training. An attractive alternative is the combination of the extrapolation power of first principles knowledge with the flexibility of machine learning methods. This approach results in a hybrid model for the growth and uptake rates that can be used to predict the dynamic operation of the bioreactor. Here we develop a hybrid model to describe the continuous production of PHA by Pseudomonas putida GPo1 culture. After training, the model with experimental data gained under different dilution rates and medium compositions, we demonstrate how the model can describe the process in a wide range of operating conditions, including both single and dual nutrient-limited growth.
Galangin Attenuates Liver Injury, Oxidative Stress and Inflammation, and Upregulates Nrf2/HO-1 Signaling in Streptozotocin-Induced Diabetic Rats
Authors: Al-Amarat Wesam , Abukhalil Mohammad H. , Althunibat Osama Y. , Alfwuaires Manal A. , Alnamshan Mashael M. , Alqosaibi Amany I. , Ahmeda Ahmad F. , Kamel Emadeldin M. , Arab Hany H. , Mahmoud Ayman M.
Published: September 2021

Chronic hyperglycemia increases the risk of liver damage. Oxidative stress and aberrant inflammatory response are entangled in diabetes-associated liver injury. This study evaluated the protective effect of the flavonoid galangin (Gal) on glucose intolerance, liver injury, oxidative stress, inflammatory response, and Nrf2/HO-1 signaling in diabetic rats. Diabetes was induced by streptozotocin (STZ), and the rats received Gal for six weeks. STZ-induced rats showed glucose intolerance, hypoinsulinemia, elevated glycated hemoglobin (HbA1c), and decreased liver glycogen. Gal ameliorated glucose intolerance, reduced HbA1c%, increased serum insulin and liver glycogen and hexokinase activity, and suppressed glycogen phosphorylase, glucose-6-phosphatase and fructose-1,6-biphosphatase in diabetic rats. Circulating transaminases, ALP and LDH, and liver ROS, MDA, TNF-α, IL-1β, and IL-6 were increased and GSH, SOD, and CAT were diminished in diabetic rats. In addition, diabetic rats exhibited multiple histopathological alterations and marked collagen deposition. Treatment with Gal mitigated liver injury, prevented histopathological alterations, decreased ROS, MDA, pro-inflammatory cytokines, Bax and caspase-3, and enhanced cellular antioxidants and Bcl-2. Gal downregulated hepatic Keap1 in diabetic rats and upregulated Nrf2 and HO-1 mRNA as well as HO-1 activity. Molecular modeling studies revealed the ability of Gal to bind to and inhibit NF-κB and Keap1, and also showed its binding pattern with HO-1. In conclusion, Gal ameliorates hyperglycemia, glucose intolerance, oxidative stress, inflammation, and apoptosis in diabetic rats. Gal improved carbohydrate metabolizing enzymes and upregulated Nrf2/HO-1 signaling.
Proton-Cluster-Beam Lethality and Mutagenicity in Bacillus subtilis Spores
Authors: Hase Yoshihiro , Satoh Katsuya , Chiba Atsuya , Hirano Yoshimi , Moribayashi Kengo , Narumi Kazumasa
Published: September 2021

The unique energy transfer characteristics of swift cluster ions have attracted the attention of many researchers working on the analysis or processing of material surfaces, but the effects on living organisms remain unclear. We irradiated B. subtilis spores with monomer and cluster proton beams and examined their lethality; the 2 MeV H2+ shows a clearly lower lethality than 340 keV H+, even though both have a comparable linear energy transfer. The 2 MeV H2+ dissociates into a pair of 1 MeV H+ by losing the bonding electrons at the target surface. The estimated internuclear distance and the radial dose distribution suggest that the spread of deposited total energy over two areas separated by just several nanometers greatly diminishes beam lethality and that the energy density in the very center of the trajectory, possibly within a 1 nm radius, has a great impact on lethality. We also performed a whole genome resequencing of the surviving colonies to compare the molecular nature of mutations but failed to find a clear difference in overall characteristics. Our results suggest that cluster beams may be a useful tool for understanding biological effects of high linear energy transfer radiation.
Correlation between Microstructural Change and Irradiation Hardening Behavior of He-Irradiated V–Cr–Ti Alloys with Low Ti Addition
Authors: Fukumoto Ken-ichi , Miura Shuichiro , Kitamura Yoshiki , Ishigami Ryoya , Nagasaka Takuya
Published: September 2021

V–4Cr–xTi (x = 0 to 4) alloys were used to investigate the additional effect of Cr, Ti and interstitial impurities on the microstructural evolution in He-irradiated V–Cr–Ti alloys to minimize radioactivity after fusion neutron irradiation. Transmission electron microscopy and atom probe tomography were carried out to the He-irradiated specimens at 500 °C with 0.5 dpa at peak damage. A flash electro-polishing method for the FIB-extracted specimen was established for the ion-irradiated vanadium alloys. The microstructural evolution of the irradiation-induced titanium-oxycarbonitride, Ti(CON) precipitates was observed and was influenced by the effect of Ti addition on the Ti(CON) precipitation. Apparent Ti(CON) precipitates formed in V-4Cr-xTi with 2% addition of Ti. In the V-4Cr-1Ti alloy, a high density Ti enriched cluster was formed. The origin of the irradiation hardening increase resulted from the size distribution of Ti(CON) precipitation from the dispersed barrier-hardening theory.
Sustainability Assessment of Reuse and Recycling Management Options for End-of-Life Computers-Korean and Japanese Case Study Analysis
Authors: Han Jaeho , Ijuin Hiromasa , Kinoshita Yuki , Yamada Tetsuo , Yamada Shuho , Inoue Masato
Published: September 2021

The depletion of natural resources and global warming have increased in severity globally. In the industrial field, assembly products, such as electronic products, should be disassembled for recycling and reuse to deal with these problems. Reuse and recycling can contribute to reducing GreenHouse Gas (GHG) emissions and less depletion of natural resources since GHG emissions for virgin material production can be saved using reused components and recycled materials. However, each component of selling revenue and material-based GHG emissions depends on the country because of the different energy mixes of electrical power. Moreover, each collected component embedded in End-of-Life (EOL) products needs to be selected as a life cycle option based on its remaining life. The purpose of this study is to decide life cycle options such as reuse, recycling, and disposal of each component environmentally-friendly and economically in Korea and Japanese cases for computers. Firstly, selecting the life cycle option for each component was formulated by 0–1 integer programming with ε constraints. Next, GHG emissions, profits, and costs in Korea and Japan were estimated and analyzed for each component. Finally, Korean and Japanese cases were analyzed to obtain an economic value in the same material-based GHG saving rate with each component’s life cycle option selection by comparing each EOL product data. In the experiments, GHG recovery efficiency was higher in Japan 43 [g/Yen] than one in Korea 28 [g/Yen]. Therefore, it was better to retrieve and reutilize the components in Korea. However, if the maximum GHG recovery efficiency is desired, Japan is a better option.
Characterising Radioactive Caesium Leaching from Incineration Ash of Municipal Solid Waste in Fukushima and the Inhibitory Effect of Acid Clay
Authors: Murasawa Naoharu
Published: September 2021

Following the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident caused by the 2011 Tōhoku earthquake and tsunami, radioactive caesium (r-Cs) was detected in the ash generated by municipal solid waste (MSW) incineration facilities in Fukushima Prefecture. This has led to concerns of r-Cs leaching and subsequent environmental contamination during recycling or landfill disposal. Therefore, it is crucial that the relevant authorities have a thorough understanding of r-Cs leaching behavior to establish suitable prevention methods. In this study, we collected r-Cs-contaminated fly and bottom ash (FA and BA) samples from five MSW incineration facilities in Fukushima Prefecture and conducted tests to clarify their basic physical properties and r-Cs leaching properties. We also examined the possibility of preventing r-Cs leaching by adding 5 wt% acid clay to the FA. FA had greater chloride content and r-Cs leaching rate than BA and was found to absorb moisture and deliquesce when stored under high-humidity conditions. However, the addition of acid clay effectively prevented r-Cs leaching upon contact with moisture. From the results, we propose some specific recommendations to counter the leaching of r-Cs from FA at MSW incineration facilities, which will limit r-Cs leaching during recycling or landfill processes.
Challenges and Emerging Trends in Toner Waste Recycling: A Review
Authors: Parthasarathy Meera
Published: September 2021

Toner waste is one of the major electronic waste materials posing serious environmental threat and health hazards. Globally, only about 20–30% of toner waste is recycled, while the remaining percentage is dumped in landfills. Recycling options are limited due to the desirably engineered durability of toners, ascribed to a complicated composition of chemicals, carbon black, and plastic particles, which in turn creates critical challenges in recycling. The World Health Organization has classified toner waste as class 2B carcinogen due to its potential health hazard. In this review, the existing challenges in toner waste recycling are discussed from the perspective of environmental, health, and feasibility aspects. In parallel, the challenges have been opening up alternative strategies to recycle toner wastes. Emerging trends in toner waste recycling include transformation of toner waste into value-added products, utilization as raw material for nanomaterial synthesis, generation of composite electrodes for power generation/storage devices, integration into construction materials, and development of microwave absorbing composites. Considering the enormous volume of toner waste generated globally every year, better recycling and transformation strategies are needed immediately. A circular economy could be established in the future by transforming the enormous toner waste into a resource for other applications. For an effective management of toner waste in the future, an integrated approach involving policies and legislations, infrastructure for collection and treatment, and financial planning among the stakeholders is needed in addition to technological innovations.
Worldviews Complexity in COVID-19 Times: Australian Media Representations of Religion, Spirituality and Non-Religion in 2020
Authors: Halafoff Anna , Marriott Emily , Smith Geraldine , Weng Enqi , Bouma Gary
Published: September 2021

In 2020, as infections of COVID-19 began to rise, Australia, alongside many other nations, closed its international borders and implemented lockdown measures across the country. The city of Melbourne was hardest hit during the pandemic and experienced the strictest and longest lockdown worldwide. Religious and spiritual groups were especially affected, given the prohibition of gatherings of people for religious services and yoga classes with a spiritual orientation, for example. Fault lines in socio-economic differences were also pronounced, with low-wage and casual workers often from cultural and religious minorities being particularly vulnerable to the virus in their often precarious workplaces. In addition, some religious and spiritual individuals and groups did not comply and actively resisted restrictions at times. By contrast, the pandemic also resulted in a positive re-engagement with religion and spirituality, as lockdown measures served to accelerate a digital push with activities shifting to online platforms. Religious and spiritual efforts were initiated online and offline to promote wellbeing and to serve those most in need. This article presents an analysis of media representations of religious, spiritual and non-religious responses to the COVID-19 pandemic in Melbourne, Australia, from January to August 2020, including two periods of lockdown. It applies a mixed-method quantitative and qualitative thematic approach, using targeted keywords identified in previous international and Australian media research. In so doing, it provides insights into Melbourne’s worldview complexity, and also of the changing place of religion, spirituality and non-religion in the Australian public sphere in COVID times.
Respect for Religiosity: Review of Faith Integration in Health and Wellbeing Interventions with Muslim Minorities
Authors: McLaren Helen , Patmisari Emi , Hamiduzzaman Mohammad , Jones Michelle , Taylor Renee
Published: September 2021

Integration of religion in community health and wellbeing interventions is important for achieving a good life among faith-based populations. In countries hosting Muslim-minorities, however, relatively little is reported in academic literature on processes of faith integration in the development and delivery of interventions. We undertook a review of peer reviewed literature on health and wellbeing interventions with Muslim-minorities, with specific interest on how Islamic principles were incorporated. Major databases were systematically searched and PRISMA guidelines applied in the selection of eligible studies. Twenty-one journal articles met the inclusion criteria. These were coded and analyzed thematically. Study characteristics and themes of religiosity are reported in this review, including the religious tailoring of interventions, content co-creation and delivery design based on the teachings from the Quran and Sunnah, and applicability of intervention structures. We reviewed the philosophical and structural elements echoing the Quran and Islamic principles in the intervention content reported. However, most studies identified that the needs of Muslim communities were often overlooked or compromised. This may be due to levels of religio-cultural knowledge of persons facilitating community health and wellbeing interventions. Our review emphasizes the importance of intellectual apparatus when working in diverse communities, effective communication-strategies, and community consultations when designing interventions with Muslim-minority communities.
New and Old Religious Minorities in International Law
Authors: Ferrari Daniele
Published: September 2021

In a time of growing transformations of the definition of religious minorities, the chapter aims to investigate the different trajectories of development of this topic in international law. To explore this issue, I propose an analysis divided into four paragraphs corresponding to the evolution of religious minorities’ rights (the traditional definition; the enlargement; the inclusion; the intersection). The chapter aims to develop the following contents: (a) an analysis of the traditional criteria defining religious minorities in international documents between 1947 and 1985; (b) a model of investigation of new religious minorities within specific trajectories of transformation of this category (implementation; inclusion; intersection); (c) a vocabulary test concerning the innovations in the linguistic approach to religious minorities; (d) the effects of the different dynamics of innovation on the rights of religious minorities.
How Buddhism Plays a Role through Victim-Offender Mediation in Handling the Challenges of Crime in China’s Tibet
Authors: Feng Lu
Published: September 2021

Religion plays a significant role in the way Western societies respond to criminal offenses. However, the research on how religion plays a role in handling the challenges of crime in non-Western countries is lacking. In this study I try to close this research gap by analyzing the victim-offender mediation in China’s Tibet, where influenced by religion, history and culture, a set of local solutions to control criminal offenses have traditionally been formed. Based on the field survey and second-hand information, I discuss how religious factors play a role in local victim-offender mediation in terms of the basis for mediation, mediator, mediation tactics, and guarantee for mediation agreement. While Buddhism acts as a form of self-control over the adherents of Buddhism, it works as a form of social control as well. Buddhist lama as the main mediator strategically uses Buddhist principles as mediation tactics in victim-offender mediation. After the mediation agreement is reached, religious ceremony is usually conducted as a guarantee. In conclusion I summarize the possible contribution of the research findings to the basic issues of restorative justice.
Automated Storey Separation and Door and Window Extraction for Building Models from Complete Laser Scans
Authors: Pexman Kate , Lichti Derek D. , Dawson Peter
Published: September 2021

Heritage buildings are often lost without being adequately documented. Significant research has gone into automated building modelling from point clouds, challenged by irregularities in building design and the presence of occlusion-causing clutter and non-Manhattan World features. Previous work has been largely focused on the extraction and representation of walls, floors, and ceilings from either interior or exterior single storey scans. Significantly less effort has been concentrated on the automated extraction of smaller features such as windows and doors from complete (interior and exterior) scans. In addition, the majority of the work done on automated building reconstruction pertains to the new-build and construction industries, rather than for heritage buildings. This work presents a novel multi-level storey separation technique as well as a novel door and window detection strategy within an end-to-end modelling software for the automated creation of 2D floor plans and 3D building models from complete terrestrial laser scans of heritage buildings. The methods are demonstrated on three heritage sites of varying size and complexity, achieving overall accuracies of 94.74% for multi-level storey separation and 92.75% for the building model creation. Additionally, the automated door and window detection methodology achieved absolute mean dimensional errors of 6.3 cm.
A Comparative Study on the Solar Radiation Pressure Modeling in GPS Precise Orbit Determination
Authors: Tang Longjiang , Wang Jungang , Zhu Huizhong , Ge Maorong , Xu Aigong , Schuh Harald
Published: September 2021

For Global Positioning System (GPS) precise orbit determination (POD), the solar radiation pressure (SRP) is the dominant nongravitational perturbation force. Among the current SRP models, the ECOM and box-wing models are widely used in the International GNSS Service (IGS) community. However, the performance of different models varies over different GPS satellites. In this study, we investigate the performances of different SRP models, including the box-wing and adjustable box-wing as a priori models, and ECOM1 and ECOM2 as parameterization models, in the GPS POD solution from 2017 to 2019. Moreover, we pay special attention to the handling of the shadow factor in the SRP modeling for eclipsing satellites, which is critical to achieve high-precision POD solutions but has not yet been fully investigated. We demonstrate that, as an a priori SRP model, the adjustable box-wing has better performance than the box-wing model by up to 5 mm in the orbit day boundary discontinuity (DBD) statistics, with the largest improvement observed on the BLOCK IIR satellites using the ECOM1 as a parameterization SRP model. The box-wing model shows an insignificant orbit improvement serving as the a priori SRP model. For the eclipsing satellites, the three-dimensional (3D) root mean square (RMS) values of orbit DBD are improved when the shadow factor is applied only in the D direction (pointing toward to Sun) than that in the three directions (D, Y, and B) in the satellite frame. Different SRP models have comparable performance in terms of the Earth rotation parameter (ERP) agreement with the IERS EOP 14C04 product, whereas the magnitude of the length of day (LoD) annual signal is reduced when the shadow factor is applied in the D direction than in the three directions. This study clarifies how the shadow factor should be applied in the GPS POD solution and demonstrates that the a priori adjustable box-wing model combined with ECOM1 is more suitable for high-precision GPS POD solutions, which is useful for the further GNSS data analysis.
ISAR Signal Tracking and High-Resolution Imaging by Kalman Filtering
Authors: Ye Pei , Xing Meng-Dao , Xia Xiang-Gen , Sun Guang-Cai , Li Yachao , Gao Yuexin
Published: September 2021

In a short observation time, after the range alignment and phase adjustment, the motion of a target can be approximated as a uniform rotation. The radar observing process can be simply described as multiplying an observation matrix on the ISAR image, which can be thought of as a linear system. It is known that the longer observation time is, the higher cross-range resolution is. In order to deal with the conflict between short observation time and high cross-range resolution, we introduce Kalman filtering (KF) into the ISAR imaging and propose a novel method to reconstruct a high-resolution image with short time observed data. As KF has excellent reconstruction performance, it leads to a good application in ISAR image reconstruction. At each observation aperture, the reconstructed image denotes the state vector in KF at the aperture time. It is corrected by a two-step KF process: prediction and update. As iteration continues, the state vector is gradually corrected to a well-focused high-resolution image. Thus, the proposed method can obtain a high-resolution image in a short observation time. Both simulated and real data are applied to demonstrate the performance of the proposed method.
Spatio-Temporal Variation Characteristics of Aboveground Biomass in the Headwater of the Yellow River Based on Machine Learning
Authors: Tang Rong , Zhao Yuting , Lin Huilong
Published: September 2021

Accurate estimation of the aboveground biomass (AGB) of grassland is a key link in understanding the regional carbon cycle. We used 501 aboveground measurements, 29 environmental variables, and machine learning algorithms to construct and verify a custom model of grassland biomass in the Headwater of the Yellow River (HYR) and selected the random forest model to analyze the temporal and spatial distribution characteristics and dynamic trends of the biomass in the HYR from 2001 to 2020. The research results show that: (1) the random forest model is superior to the other three models (R2val = 0.56, RMSEval = 51.3 g/m2); (2) the aboveground biomass in the HYR decreases spatially from southeast to northwest, and the annual average value and total values are 176.8 g/m2 and 20.73 Tg, respectively; (3) 69.51% of the area has shown an increasing trend and 30.14% of the area showed a downward trend, mainly concentrated in the southeast of Hongyuan County, the northeast of Aba County, and the north of Qumalai County. The research results can provide accurate spatial data and scientific basis for the protection of grassland resources in the HYR.
Two-Stream Convolutional Long- and Short-Term Memory Model Using Perceptual Loss for Sequence-to-Sequence Arctic Sea Ice Prediction
Authors: Chi Junhwa , Bae Jihyun , Kwon Young-Joo
Published: September 2021

Arctic sea ice plays a significant role in climate systems, and its prediction is important for coping with global warming. Artificial intelligence (AI) has gained recent attention in various disciplines with the increasing use of big data. In recent years, the use of AI-based sea ice prediction, along with conventional prediction models, has drawn attention. This study proposes a new deep learning (DL)-based Arctic sea ice prediction model with a new perceptual loss function to improve both statistical and visual accuracy. The proposed DL model learned spatiotemporal characteristics of Arctic sea ice for sequence-to-sequence predictions. The convolutional neural network-based perceptual loss function successfully captured unique sea ice patterns, and the widely used loss functions could not use various feature maps. Furthermore, the input variables that are essential to accurately predict Arctic sea ice using various combinations of input variables were identified. The proposed approaches produced statistical outcomes with better accuracy and qualitative agreements with the observed data.
Urban Building Extraction and Modeling Using GF-7 DLC and MUX Images
Authors: Luo Heng , He Biao , Guo Renzhong , Wang Weixi , Kuai Xi , Xia Bilu , Wan Yuan , Ma Ding , Xie Linfu
Published: September 2021

Urban modeling and visualization are highly useful in the development of smart cities. Buildings are the most prominent features in the urban environment, and are necessary for urban decision support; thus, buildings should be modeled effectively and efficiently in three dimensions (3D). In this study, with the help of Gaofen-7 (GF-7) high-resolution stereo mapping satellite double-line camera (DLC) images and multispectral (MUX) images, the boundary of a building is segmented via a multilevel features fusion network (MFFN). A digital surface model (DSM) is generated to obtain the elevation of buildings. The building vector with height information is processed using a 3D modeling tool to create a white building model. The building model, DSM, and multispectral fused image are then imported into the Unreal Engine 4 (UE4) to complete the urban scene level, vividly rendered with environmental effects for urban visualization. The results of this study show that high accuracy of 95.29% is achieved in building extraction using our proposed method. Based on the extracted building vector and elevation information from the DSM, building 3D models can be efficiently created in Level of Details 1 (LOD1). Finally, the urban scene is produced for realistic 3D visualization. This study shows that high-resolution stereo mapping satellite images are useful in 3D modeling for urban buildings and can support the generation and visualization of urban scenes in a large area for different applications.
Solar Resource Potentials and Annual Capacity Factor Based on the Korean Solar Irradiance Datasets Derived by the Satellite Imagery from 1996 to 2019
Authors: Kim Chang Ki , Kim Hyun-Goo , Kang Yong-Heack , Yun Chang-Yeol , Kim Boyoung , Kim Jin Young
Published: September 2021

The Korea Institute of Energy Research builds Korean solar irradiance datasets, using gridded solar insolation estimates derived using the University of Arizona solar irradiance based on Satellite–Korea Institute of Energy Research (UASIBS–KIER) model, with the incorporation of geostationary satellites over the Korean Peninsula, from 1996 to 2019. During the investigation period, the monthly mean of daily total irradiance was in a good agreement with the in situ measurements at 18 ground stations; the mean absolute error is also normalized to 9.4%. It is observed that the irradiance estimates in the datasets have been gradually increasing at a rate of 0.019 kWh m−2 d−1 per year. The monthly variation in solar irradiance indicates that the meteorological conditions in the spring season dominate the annual solar insolation. In addition, the local distribution of solar irradiance is primarily affected by the geographical environment; higher solar insolation is observed in the southern part of Korea, but lower solar insolation is observed in the mountainous range in Korea. The annual capacity factor is the secondary output from the Korean solar irradiance datasets. The reliability of the estimate of this factor is proven by the high correlation coefficient of 0.912. Thus, in accordance with the results from the spatial distribution of solar irradiance, the southern part of Korea is an appropriate region for establishing solar power plants exhibiting a higher annual capacity factor than the other regions.
The Relative Contributions of Climate and Grazing on the Dynamics of Grassland NPP and PUE on the Qinghai-Tibet Plateau
Authors: Yu Huilin , Ding Qiannan , Meng Baoping , Lv Yanyan , Liu Chang , Zhang Xinyu , Sun Yi , Li Meng , Yi Shuhua
Published: September 2021

Net primary productivity (NPP) and precipitation-use efficiency (PUE) are crucial indicators in understanding the responses of vegetation to global change. However, the relative contributions of climate change and human interference to the dynamics of NPP and PUE remain unclear. During the past few decades, the impacts of climate change and human activities on alpine grasslands on the Qinghai-Tibet Plateau (QTP) have been intensifying. The aims of the study were to investigate the spatiotemporal patterns of grassland NPP and PUE on the QTP during 2000–2017 and quantify how much of the variance in NPP and PUE can be attributed to the climatic factors (precipitation and temperature) and grazing intensity. The results showed that: (1) grassland NPP significantly increased with a rate of 0.6 g C m−2 year−1 over the past 18 years, mainly induced by the increased temperature and the enhanced precipitation. The temperature was the dominant factor for NPP interannual variation in mid-eastern QTP, and precipitation restrained vegetation growth most in the southwest and northeast. (2) The PUE was higher on the eastern and western parts of the plateau, but lower at the center. Regarding grassland types, the PUE of alpine steppe (0.19 g C m−2 mm−1) was significantly lower than those of alpine meadow (0.31 g C m−2 mm−1) and desert steppe (0.32 g C m−2 mm−1). (3) Precipitation was significantly and negatively correlated with PUE and contributed the most to the temporal variation of grassland PUE on the QTP (52.7%). (4) Furthermore, we found that the grazing activities had the lowest contributions to both NPP and PUE interannual variation, compared to temperature and precipitation. Thus, it is suggested that climate variability rather than grazing activities dominated vegetation changes on the QTP.
An Image Registration Method Using Deep Residual Network Features for Multisource High-Resolution Remote Sensing Images
Authors: Zhao Xin , Li Hui , Wang Ping , Jing Linhai
Published: September 2021

Accurate registration for multisource high-resolution remote sensing images is an essential step for various remote sensing applications. Due to the complexity of the feature and texture information of high-resolution remote sensing images, especially for images covering earthquake disasters, feature-based image registration methods need a more helpful feature descriptor to improve the accuracy. However, traditional image registration methods that only use local features at low levels have difficulty representing the features of the matching points. To improve the accuracy of matching features for multisource high-resolution remote sensing images, an image registration method based on a deep residual network (ResNet) and scale-invariant feature transform (SIFT) was proposed. It used the fusion of SIFT features and ResNet features on the basis of the traditional algorithm to achieve image registration. The proposed method consists of two parts: model construction and training and image registration using a combination of SIFT and ResNet34 features. First, a registration sample set constructed from high-resolution satellite remote sensing images was used to fine-tune the network to obtain the ResNet model. Then, for the image to be registered, the Shi_Tomas algorithm and the combination of SIFT and ResNet features were used for feature extraction to complete the image registration. Considering the difference in image sizes and scenes, five pairs of images were used to conduct experiments to verify the effectiveness of the method in different practical applications. The experimental results showed that the proposed method can achieve higher accuracies and more tie points than traditional feature-based methods.
Tree Extraction from Airborne Laser Scanning Data in Urban Areas
Authors: You Hangkai , Li Shihua , Xu Yifan , He Ze , Wang Di
Published: September 2021

Tree information in urban areas plays a significant role in many fields of study, such as ecology and environmental management. Airborne LiDAR scanning (ALS) excels at the fast and efficient acquisition of spatial information in urban-scale areas. Tree extraction from ALS data is an essential part of tree structural studies. Current raster-based methods that use canopy height models (CHMs) suffer from the loss of 3D structure information, whereas the existing point-based methods are non-robust in complex environments. Aiming at making full use of the canopy’s 3D structure information that is provided by point cloud data, and ensuring the method’s suitability in complex scenes, this paper proposes a new point-based method for tree extraction that is based on 3D morphological features. Considering the elevation deviations of the ALS data, we propose a neighborhood search method to filter out the ground and flat-roof points. A coarse extraction method, combining planar projection with a point density-filtering algorithm is applied to filter out distracting objects, such as utility poles and cars. After that, a Euclidean cluster extraction (ECE) algorithm is used as an optimization strategy for coarse extraction. In order to verify the robustness and accuracy of the method, airborne LiDAR data from Zhangye, Gansu, China and unmanned aircraft vehicle (UAV) LiDAR data from Xinyang, Henan, China were tested in this study. The experimental results demonstrated that our method was suitable for extracting trees in complex urban scenes with either high or low point densities. The extraction accuracy obtained for the airborne LiDAR data and UAV LiDAR data were 99.4% and 99.2%, respectively. In addition, a further study found that the aberrant vertical structure of the artificially pruned canopy was the main cause of the error. Our method achieved desirable results in different scenes, with only one adjustable parameter, making it an easy-to-use method for urban area studies.
Classification of Plant Ecological Units in Heterogeneous Semi-Steppe Rangelands: Performance Assessment of Four Classification Algorithms
Authors: Aghababaei Masoumeh , Ebrahimi Ataollah , Naghipour Ali Asghar , Asadi Esmaeil , Verrelst Jochem
Published: September 2021

Plant Ecological Unit’s (PEUs) are the abstraction of vegetation communities that occur on a site which similarly respond to management actions and natural disturbances. Identification and monitoring of PEUs in a heterogeneous landscape is the most difficult task in medium resolution satellite images datasets. The main objective of this study is to compare pixel-based classification versus object-based classification for accurately classifying PEUs with four selected different algorithms across heterogeneous rangelands in Central Zagros, Iran. We used images of Landsat-8 OLI that were pan-sharpened to 15 m to classify four PEU classes based on a random dataset collected in the field (40%). In the first stage, we applied the following classification algorithms to distinguish PEUs: Minimum Distance (MD), Maximum Likelihood Classification (MLC), Neural Network-Multi Layer Perceptron (NN-MLP) and Classification Tree Analysis (CTA) for pixel based method and object based method. Then, by using the most accurate classification approach, in the second stage auxiliary data (Principal Component Analysis (PCA)) was incorporated to improve the accuracy of the PEUs classification process. At the end, test data (60%) were used for accuracy assessment of the resulting maps. Object-based maps clearly outperformed pixel-based maps, especially with CTA, NN-MLP and MD algorithms with overall accuracies of 86%, 72% and 59%, respectively. The MLC algorithm did not reveal any significant difference between the object-based and pixel-based analyses. Finally, complementing PCA auxiliary bands to the CTA algorithms offered the most successful PEUs classification strategy, with the highest overall accuracy (89%). The results clearly underpin the importance of object-based classification with the CTA classifier together with PCA auxiliary data to optimize identification of PEU classes.