bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Fluorinated Polyurethane Binder on the Agglomeration Behaviors of Aluminized Propellants
Authors: Shen Chen , Yan Shi , Ou Yapeng , Jiao Qingjie
Published: March 2022

In this study, fluorinated polyurethane (FPU) was prepared from dialcohol-terminated perfluoropolyether as a soft segment; isophorone diisocyanate (IPDI) as a curing agent; 1,2,4-butanetriol (BT) as a crosslinker; and 1,4-butanediol (BDO) as a chain extender. Fourier transform infrared spectroscopy (FTIR) and 1H NMR were used to characterize the structure of the FPU. The mechanical properties of the FPUs with different BDO and BT contents were also measured. The tensile strength and breaking elongation of the optimized FPU formula were 3.7 MPa and 412%, respectively. To find out the action mechanism of FPU on Al, FPU/Al was prepared by adding Al directly to FPU. The thermal decomposition of the FPU and FPU/Al was studied and compared by simultaneous differential scanning calorimetry-thermogravimetry-mass spectrometry (DSC-TG-MS). It was found that FPU can enhance the oxidation of Al by altering the oxide-shell properties. The combustion performance of the FPU propellant, compared with the corresponding hydroxyl-terminated polyether (HTPE)-based polyurethane (HPU) propellant, was recorded by a high-speed video camera. The FPU propellants were found to produce smaller agglomerates due to the generation of AlF3 in the combustion process. These findings show that FPU may be a useful binder for tuning the agglomeration and reducing two-phase flow losses of aluminized propellants.
Current Research and Applications of Starch-Based Biodegradable Films for Food Packaging
Authors: Onyeaka Helen , Obileke KeChrist , Makaka Golden , Nwokolo Nwabunwanne
Published: March 2022

The use of biodegradable packaging material as an alternative to conventional petrochemical-based polymers is based on the environmental issues associated with conventional materials. This review aims to update the existing knowledge regarding the application of starch-based biodegradable films for food packaging. From the review, it was evident that starch stands out among biopolymers due to its abundance and cost effectiveness. This review is the first of its kind, having reviewed over 100 articles/publications on starch-based biodegradable films, consolidating their current state of research and their applications for food packaging; therefore, this review provides an insight into the utilization of nanomaterials to improve the shelf life of packaging of food.
Functionalized Hemodialysis Polysulfone Membranes with Improved Hemocompatibility
Authors: Radu Elena Ruxandra , Voicu Stefan Ioan
Published: March 2022

The field of membrane materials is one of the most dynamic due to the continuously changing requirements regarding the selectivity and the upgradation of the materials developed with the constantly changing needs. Two membrane processes are essential at present, not for development, but for everyday life—desalination and hemodialysis. Hemodialysis has preserved life and increased life expectancy over the past 60–70 years for tens of millions of people with chronic kidney dysfunction. In addition to the challenges related to the efficiency and separative properties of the membranes, the biggest challenge remained and still remains the assurance of hemocompatibility—not affecting the blood during its recirculation outside the body for 4 h once every two days. This review presents the latest research carried out in the field of functionalization of polysulfone membranes (the most used polymer in the preparation of membranes for hemodialysis) with the purpose of increasing the hemocompatibility and efficiency of the separation process itself with a decreasing impact on the body.
Solution-Processable Colorless Polyimides Derived from Hydrogenated Pyromellitic Dianhydride: Strategies to Reduce the Coefficients of Thermal Expansion by Maximizing the Spontaneous Chain Orientation Behavior during Solution Casting
Authors: Hasegawa Masatoshi , Ichikawa Katsuki , Takahashi Shuichi , Ishii Junichi
Published: March 2022

In this study, practically useful colorless polyimides (PIs) with low coefficients of thermal expansion (CTEs) and other desirable properties were prepared from hydrogenated pyromellitic dianhydride (1-exo,2-exo,4-exo,5-exo-cyclohexanetetracarboxylic dianhydride, H-PMDA). A modified one-pot polymerization method afforded a high-molecular-weight PI with sufficient film-forming ability from 2,2′-bis(trifluoromethyl)benzidine (TFMB) with a rod-like structure and H-PMDA. However, the PI film cast from its homogeneous solution did not have low CTEs, similar to the analogous system using meta-tolidine. To solve this problem, a series of amide- and amide-imide-containing diamines were designed and synthesized. The modified one-pot polymerization of H-PMDA and the diamines in γ-butyrolactone produced homogeneous, viscous, and stable solutions of high-molecular-weight PIs with high solid contents. The cast films of certain systems examined in this study simultaneously achieved low CTEs, high optical transparency, considerably high glass transition temperatures (Tgs), and sufficient ductility. A possible mechanism for the generation of low CTEs, which is closely related to the spontaneous in-plane orientation behavior during solution casting, was proposed. Certain H-PMDA-based PIs developed in this study are promising colorless heat-resistant plastic substrates for use in image display devices and other optical applications.
Layered-Fabric Materiality Fibre Reinforced Polymers (L-FMFRP): Hysteretic Behavior in Architectured FRP Material
Authors: Blonder Arielle , Brocato Maurizio
Published: March 2022

L_FMFRP is an architectural fiber composite surface element with an airy internal structure and variable section. This architectured material is the product of an alternative design and fabrication process that integrates fabric materiality, suggesting moldless shaping of the material through pleating and layering. Initial study of the mechanical properties of the element showed a structural behavior that would satisfy the requirement for schematic architectural cladding configurations, indicating a unique hysteretic behavior of the material. This paper further investigates the hysteretic capacities of L-FMFRP, examining the behavior under repeated loading and the effect of its internal material architecture. Parallels to entangled materials are suggested for a deeper understanding of the phenomenon, and the potential future application as an energy-absorbent material for façade cladding is outlined.
The Effect of Alkaline Treatment on Poly(lactic acid)/Date Palm Wood Green Composites for Thermal Insulation
Authors: Al Abdallah Hyder , Abu-Jdayil Basim , Iqbal Muhammad Z.
Published: March 2022

In this work, the effect of alkaline treatment on the thermal insulation and mechanical properties of date palm wood fibers (DPWF) and polylactic acid (PLA) green composite was studied. Alkaline treatment was applied to DPWF using two different solutions: sodium hydroxide (NaOH) and potassium hydroxide (KOH), with concentration of 2 vol.%. The fibers were later incorporated into PLA with weight percentages from 10 to 40 wt.%, to form three composite types: PLA with untreated fibers (PLA-UTDPWF), PLA with KOH treated fibers (PLA-KOH), and PLA with NaOH treated fibers (PLA-NaOH). The prepared composites were for use as a green thermal insulation material. The composites were tested to assess the effect of treatment on their physical (density and degree of crystallization), thermal (thermal conductivity, specific heat capacity, thermal diffusivity, thermal degradation, glass transition, and melting temperature), and mechanical properties. Moreover, the composite structural characteristics were investigated using FTIR and SEM analysis. The alkaline treatment significantly increased the crystallinity of the composites, specifically for higher filler loadings of 30 and 40 wt.%. The crystallinity for the 40 wt.% increased from 33.2% for PLA-UTDPWF, to 41% and 51%, for PLA-NaOH and PLA-KOH, respectively. Moreover, the alkaline treatment reduced the density and produced lighter composites than the untreated specimens. For instance, the density of 40 wt.% composite was reduced from 1.43, to 1.22 and 1.30 gcm3 for PLA-NaOH and PLA-KOH, respectively.
The Synergetic Impact of Anionic, Cationic, and Neutral Polymers on VES Rheology at High-Temperature Environment
Authors: Othman Amro , AlSulaimani Mohammed , Aljawad Murtada Saleh , Sangaru Shiv Shankar , Kamal Muhammad Shahzad , Mahmoud Mohamed
Published: March 2022

Hydraulic fracturing operations target enhancing the productivity of tight formations through viscous fluid injection to break down the formation and transport proppant. Crosslinked polymers are usually used for desired viscoelasticity of the fracturing fluid; however, viscoelastic surfactants (VES) became a possible replacement due to their less damaging impact. To design a fracturing fluid with exceptional rheological and thermal stability, we investigated mixing zwitterionic VES with carboxymethyl cellulose (CMC), hydroxyethylcellulose (HEC), or a poly diallyl dimethylammonium chloride (DADMAC) polymers. As a base fluid, calcium chloride (CaCl2) solution was prepared with either distilled water or seawater before adding a polymer and the VES. A Chandler high-pressure, high-temperature (HPHT) viscometer was used to conduct the viscosity measurements at a shear rate of 100 1/s. It has been found that adding 1% CMC polymer to 9% (v/v) VES increases the viscosity more compared to 10% (v/v) VES at reservoir temperatures of 143.3 °C. On the other hand, adding only 1.0% of HEC to 9% (v/v) VES doubled the viscosity and proved more effective than adding CMC. HEC, nevertheless, reduced the system stability at high temperatures (i.e., 148.9 °C). Adding DADMAC polymer (DP) to VES increased the system viscosity and maintained high stability at high temperatures despite being exposed to saltwater. CaCl2 concentration was also shown to affect rheology at different temperatures. The improved viscosity through the newly designed polymer can reduce chemical costs (i.e., reducing VES load), making it more efficient in hydraulic fracturing operations.
Torsional Vibration Tests of Extruded Polystyrene with Improved Accuracy in Determining the Shear Modulus
Authors: Yoshihara Hiroshi , Wakahara Momoka , Yoshinobu Masahiro , Maruta Makoto
Published: March 2022

Recently, extruded polystyrene (XPS) foam has been used as a component of construction materials; therefore, it is important to characterize its mechanical properties, including shear modulus. Despite the importance, it is often difficult to determine the shear modulus accurately by using many of the conventional methods; therefore, it is desirable to establish another method to measure the shear modulus with a high accuracy. Among various methods, torsional vibration test is advantageous because it can be performed easily under the pure shear stress condition in the test sample and both the in-plane and out-of-plane shear moduli can be obtained. However, it is difficult to find any examples performing the torsional vibration tests. In this study, the in-plane and out-of-plane shear moduli of XPS were determined through torsional vibration tests using samples of various widths. In addition, the shear moduli were also determined through flexural vibration tests and compared with those obtained from the torsional vibration tests. In the torsional vibration tests, the anisotropy in these shear moduli became an obstacle, and the in-plane shear modulus determined using a single sample was often dependent on the width/thickness ratio of the sample. In this condition, the coefficient of variation of the in-plane shear modulus value was often close to 10%. However, when using data obtained from the samples with various width/thickness ratios, both the in-plane and out-of-plane shear moduli could be obtained while reducing the abovementioned dependence. Additionally, the coefficients of variation were restricted to those below 2% and 7% for the in-plane and out-of-plane shear moduli, respectively, and these values were obviously lower than those obtained from the flexural vibration tests (approximately 20%). In the proposed method, both the in-plane and out-of-plane shear moduli can be obtained accurately without using any numerical analyses, which are often required in the standardized methods to improve the accuracy. Thus, for accurate measurement of both types of shear moduli of XPS, we recommend performing torsional vibration tests using a range of samples of various width/thickness ratios.
Effect of the High-Pressure Hydrogen Gas Exposure in the Silica-Filled EPDM Sealing Composites with Different Silica Content
Authors: Kang Hyun Min , Choi Myung Chan , Lee Jin Hyok , Yun Yu Mi , Jang Jin Sub , Chung Nak Kwan , Jeon Sang Koo , Jung Jae Kap , Lee Ji Hun , Lee Jin Hong , Chang Young Wook , Bae Jong Woo
Published: March 2022

With the increasing interest in hydrogen energy, the stability of hydrogen storage facilities and components is emphasized. In this study, we analyzed the effect of high-pressure hydrogen gas treatment in silica-filled EPDM composites with different silica contents. In detail, cure characteristics, crosslink density, mechanical properties, and hydrogen permeation properties were investigated. Results showed that material volume, remaining hydrogen content, and mechanical properties were changed after 96.3 MPa hydrogen gas exposure. With an increase in the silica content, the crosslink density and mechanical properties increased, but hydrogen permeability was decreased. After treatment, high-silica-content composites showed lower volume change than low-silica-content composites. The crack damage due to the decompression caused a decrease in mechanical properties, but high silica content can inhibit the reduction in mechanical properties. In particular, EPDM/silica composites with a silica content of above 60 phr exhibited excellent resistance to hydrogen gas, as no change in their physical and mechanical properties was observed.
Experimental and Numerical Validation of the One-Process Modeling Approach for the Hydration of K2CO3 Particles
Authors: Beving Max , Romme Joris , Donkers Pim , Frijns Arjan , Rindt Camilo , Smeulders David
Published: March 2022

Potassium carbonate (K2CO3) is a promising material for the long-term storage of renewable energy. A reactor vessel filled with K2CO3 can potentially be used as a domestic heat battery. The hydration and dehydration reactions of salt hydrates in a reactor vessel are generally described using a one-process model, such as the ‘Arrhenius-f(α)’ model. However, this modeling approach cannot always be applied correctly. If the reaction does not proceed in a pseudo-steady state, and/or when nucleation and growth processes are simultaneously active during the transformation from an anhydrous to a hydrated state, the one-process modeling approach should not be applied. In this paper, it is investigated using simultaneous thermal analysis (STA) experiments whether the pseudo-steady state approximation is valid during the hydration reaction of K2CO3. Additionally, ‘jump experiments’ using STA are employed to investigate the rate-determining step (RDS) of the hydration reaction by applying step-wise changes in partial water vapor pressure. The presence of nucleation and growth processes during the hydration reaction is investigated by fitting isotropic models to STA data. The STA results showed that indeed the hydration of K2CO3 happens in a pseudo-steady state, and the reaction can be described using a RDS. An isotropic nucleation and growth model shows that the hydration reaction can be described by assuming instantaneous nucleation followed by diffusion-limited growth. This leads to the general conclusion that the one-process modeling approach, such as the Arrhenius-f(α) model, is valid to describe the hydration reaction of K2CO3 particles.
Optimization of a Tricalcium Phosphate-Based Bone Model Using Cell-Sheet Technology to Simulate Bone Disorders
Authors: Damerau Alexandra , Buttgereit Frank , Gaber Timo
Published: March 2022

Bone diseases such as osteoporosis, delayed or impaired bone healing, and osteoarthritis still represent a social, financial, and personal burden for affected patients and society. Fully humanized in vitro 3D models of cancellous bone tissue are needed to develop new treatment strategies and meet patient-specific needs. Here, we demonstrate a successful cell-sheet-based process for optimized mesenchymal stromal cell (MSC) seeding on a β-tricalcium phosphate (TCP) scaffold to generate 3D models of cancellous bone tissue. Therefore, we seeded MSCs onto the β-TCP scaffold, induced osteogenic differentiation, and wrapped a single osteogenically induced MSC sheet around the pre-seeded scaffold. Comparing the wrapped with an unwrapped scaffold, we did not detect any differences in cell viability and structural integrity but a higher cell seeding rate with osteoid-like granular structures, an indicator of enhanced calcification. Finally, gene expression analysis showed a reduction in chondrogenic and adipogenic markers, but an increase in osteogenic markers in MSCs seeded on wrapped scaffolds. We conclude from these data that additional wrapping of pre-seeded scaffolds will provide a local niche that enhances osteogenic differentiation while repressing chondrogenic and adipogenic differentiation. This approach will eventually lead to optimized preclinical in vitro 3D models of cancellous bone tissue to develop new treatment strategies.
Technology Trend Forecasting and Technology Opportunity Discovery Based on Text Mining: The Case of Refrigerated Container Technology
Authors: Wang Yansen , Feng Lijie , Wang Jinfeng , Zhao Huadong , Liu Peng
Published: March 2022

How to detect potential useful technical information hidden in patents and scientific papers is crucial for technology trend forecasting and potential research opportunities. Using the text mining method to extract hidden technical information is helpful in assisting strategic decision-making and predicting the tendency of technological development. This study proposes a framework to combine patent analysis and scientific paper analysis to predict technology trends and discover technology opportunities. By mining the hidden technical information, we compared an analysis of patents and scientific papers to reveal the technological development trajectory and future development trends and discover potential technological innovation opportunities. First, we extracted the knowledge contained in patents and scientific papers by text mining. Then, we cleaned and coded the data through natural language processing. We used the Latent Dirichlet Allocation topic model to cluster topics and list the multi-dimensional hierarchical structure diagram. We compared and analyzed results, combined them with expert knowledge, and drew a technology roadmap to predict future development trends and discover technological opportunities. Finally, we used refrigerated container technology as an example for validation. Results showed that the framework proposed in this study can directly and comprehensively display the development trend of technology and discover potential technological innovation opportunities to verify the effectiveness of the framework. The proposed method also provides an effective reference and inspiration for future research.
Non-Thermal Atmospheric Plasma for Microbial Decontamination and Removal of Hazardous Chemicals: An Overview in the Circular Economy Context with Data for Test Applications of Microwave Plasma Torch
Authors: Todorova Yovana , Benova Evgenia , Marinova Plamena , Yotinov Ivaylo , Bogdanov Todor , Topalova Yana
Published: March 2022

The transformation of our linear “take-make-waste” system to a cyclic flow of materials and energy is a priority task for society, but the circular use of waste streams from one industry/sector as a material input for another must be completely safe. The need for new advanced technologies and methods ensuring both microbiological safety and the removal of potential chemical residues in used materials and products is urgent. Non-thermal atmospheric plasma (cold atmospheric plasma—CAP) has recently attracted great research interest as an alternative for operative solutions of problems related to safety and quality control. CAP is a powerful tool for the inactivation of different hazardous microorganisms and viruses, and the effective decontamination of surfaces and liquids has been demonstrated. Additionally, the plasma’s active components are strong oxidizers and their synergetic effect can lead to the degradation of toxic chemical compounds such as phenols and azo-dyes.
Analysis and Implementation of a Bidirectional Converter with Soft Switching Operation
Authors: Lin Bor-Ren
Published: March 2022

This paper presents a soft switching direct current (DC) converter, with the benefits of bidirectional power conversion and wide-ranging voltage operation for battery charging and discharging capability. A series resonant circuit with variable switching frequency modulation is used to achieve the advantages of soft switching turn-on or turn-off of semiconductor devices. Therefore, the switching power losses in power devices can be reduced. A symmetric resonant circuit topology with a capacitor–inductor–inductor–capacitor (CLLC) structure is adopted to achieve a bidirectional power conversion capability for battery storage units in electric vehicle applications. Due to the symmetric circuit structure on both input and output sides, the converter has similar voltage gains for each power flow operation. In order to overcome the drawback of narrow voltage range operation in conventional resonant converters, a variable transformer turns ratio is adopted in the circuit, to achieve wide output voltage operation (150–450 V) for battery charging applications. To demonstrate the converter performance, a 1-kW laboratory prototype was constructed and tested. Experimental results are provided, to verify the effectiveness of the studied circuit.
From Collective Shiva to a Fast for the Ages: Religious Initiatives to Commemorate and Mourn the Victims of the Holocaust, 1944–1951
Authors: Yedidya Asaf
Published: March 2022

Religious Jewish tradition has specific rituals for mourning the loss of a relative. They include receiving visitors during shiva, the recitation of the Kaddish in the first year, and the annual marking of the Yahrzeit. There are also customs for commemorating collective disasters. Foremost among them are the diminution of joy on specific dates, and setting permanent fast days. Towards the end of World War II, when the extent of the destruction became apparent, initiatives began around the world to process the collective mourning and to perpetuate the disaster in religious settings. Many survivors later joined these initiatives, seeking to establish new customs, out of a deep sense that this was an unprecedented calamity. The growing need to combine private and collective mourning stemmed from an awareness of the psychological and cultural power of private mourning customs. Proposals therefore included the observance of a community yahrzeit, a collective Jewish shiva, along with a fast for the ages. This article explores the initiatives undertaken between 1944 and 1951—the time when intensive processing was needed for the survivors and the relatives of those who had perished—discussing their motivations, unique characteristics, successes and failures, and the reasons for them.
Responding to a Weeping Planet: Practical Theology as a Discipline Called by Crisis
Authors: Moore Mary Elizabeth
Published: March 2022

Practical theology is by nature a discipline of crisis, standing on the edge of reality and potential, what is and what can be. Crises can be gentle turning points, opportunities for radical transformation, or catastrophic moments in time. In the geological age of the Anthropocene, people face devastating planetary effects of human agency, which have created and escalated a climate crisis beyond the boundaries of imagination. Practical theology belongs at the epicenter of ecological crises, which have already produced harsh results, ecological despair, and a time-dated urgency for daring decisions and actions. Change is knocking at global doors—the necessity, foreboding, and hope for change. This article probes practical theology’s role in change, giving primary attention to changes in practical wisdom (phronesis) and life practices. Methodologically, the article draws from ecological scholars and activists, philosophers and theologians, indigenous communities, and the earth itself, presenting descriptions and analyses of their shared wisdom across time, culture, and areas of expertise. From these sources, the study identifies challenges, practices, and alternate worldviews that can potentially reshape practical wisdom and climate action. In conclusion, this paper proposes life practices for climate justice: practices of attending, searching, imagining, and communal living and acting.
Digital Technologies in Arctic Oil and Gas Resources Extraction: Global Trends and Russian Experience
Authors: Samylovskaya Ekaterina , Makhovikov Alexey , Lutonin Alexander , Medvedev Dmitry , Kudryavtseva Regina-Elizaveta
Published: March 2022

The paper is devoted to the analysis of the current and the forecast of the prospective state of introducing digital technologies into the oil and gas mining industry of the Russian Arctic. The authors of the paper analyzed the global trends that define the process of digital technologies’ introduction into the oil and gas mining industry. They also reviewed the Russian companies’ experience in this sphere. The main trends and prospects for the development of oil and gas resources extraction in the Russian Arctic in the digitalization sphere were identified. Together with this, the researchers considered prospects for digital technologies’ introduction into the oil and gas industry, observing their competition with RES. As a result, the authors have come to the following conclusions: (1) in Russian companies, digitalization is being more actively introduced into the processes of general enterprise management. (2) The main purpose of Russian oil and gas sector digitalization is to increase the efficiency of business process management, while the key constraining factors of digitalization are the lack of qualified personnel, lack of material and technical base and cyber-security threats aggravation. (3) The prospects of introducing a new package of sanctions can become both an incentive for a qualitative leap in Russian software development/implementation and an obstacle to the development of Arctic projects due to their rise in price. (4) The COVID-19 pandemic factor is one of the incentives for the widespread introduction of production and various business processes automation in the oil and gas industry, as well as the development of digital communications. (5) The leader in the digital technology development industry among Russian oil and gas companies is “Gazprom Neft” PJSC, followed by “NK Rosneft” PJSC. (6) “Gazprom” PJSC continues to lag behind in the sphere of digitalization; however, qualitative changes here should be expected in 2022. (7) The “sensitivity parameters” influencing the industry digitalization process in the Arctic region are the high dependence on foreign technological solutions and software, characteristics of the entire Russian oil and gas industry, and the problem of ensuring cybersecurity in Arctic oil and gas projects and power outages. (8) For the Arctic regions, the use of RES as the main source of electricity is the most optimal and promising solution; however, hydrocarbon energy will still dominate the market in the foreseeable future.
Environmental, Social and Governance Credentials of Agricultural Companies—The Interplay with Company Size
Authors: Cristea Mirela , Noja Graţiela Georgiana , Thalassinos Eleftherios , Cîrciumaru Daniel , Ponea Constantin Ștefan , Durău Carmen Claudia
Published: March 2022

Based on the significance of the corporate social responsibility (CSR) activities, respectively, the Environmental, Social and Governance (ESG) measures, for companies’ advancement in the fields of agriculture, the purpose of our study is to appraise how the ESG measures influence the size of public companies from the agricultural sectors, with particular attention on the environmental pillar. The research methodology consists in applying two econometric procedures to assess the direct effects of the ESG activities on the size of public agricultural firms by models of robust regression (RREG) and to appraise global implications of ESG measures on companies’ dimension by models of structural equations (SEM). Data encloses the ESG indicators, focusing on environmental indicators and agricultural companies’ size (proxied by total assets), extracted from the Thomson Reuters Refinitiv Eikon database for the fiscal year 2020. Main results reveal that several components of the ESG measures, especially the environmental ones, may influence the size of the agricultural companies, given the significant companies’ strengths in implementing CSR actions to ensure sustainable resource management. We propose adequate strategies for companies to provide robust resource management and proper integration of the environmental credentials.
The Effect of Autotrophic Cultivation of Platymonas subcordiformis in Waters from the Natural Aquatic Reservoir on Hydrogen Yield
Authors: Dudek Magda , Dębowski Marcin , Nowicka Anna , Kazimierowicz Joanna , Zieliński Marcin
Published: March 2022

Biological processes run by microalgae are prospective but still little known methods of hydrogen production. A prerequisite for their increased advancement is the development of economically viable and efficient technologies. The study presented in this manuscript focused on determining the efficiency of biohydrogen production by P. subcordiformis using a culture medium prepared based on natural waters. The rate of P. subcordiformis biomass growth reached 317.6 ± 42.3 mgODM/dm3·d and ensured a biomass concentration of 3493 ± 465 mgODM/dm3. The percentage concentration of hydrogen in the biogas reached 63.2 ± 1.4%, and its production rate ranged from 0.53 ± 0.05 cm3/h to 0.70 ± 0.01 cm3/h.
Forecast of the Global TEC by Nearest Neighbour Technique
Authors: Monte-Moreno Enric , Yang Heng , Hernández-Pajares Manuel
Published: March 2022

We propose a method for Global Ionospheric Maps of Total Electron Content forecasting using the Nearest Neighbour method. The assumption is that in a database of global ionosphere maps spanning more than two solar cycles, one can select a set of past observations that have similar geomagnetic conditions to those of the current map. The assumption is that the current ionospheric condition can be expressed by a linear combination of conditions seen in the past. The average of these maps leads to common geomagnetic components being preserved and those not shared by several maps being reduced. The method is based on searching the historical database for the dates of the maps closest to the current map and using as a prediction the maps in the database that correspond to time shifts on the prediction horizons. In contrast to other methods of machine learning, the implementation only requires a distance computation and does not need a previous step of model training and adjustment for each prediction horizon. It also provides confidence intervals for the forecast. The method has been analyzed for two full years (2015 and 2018), for selected days of 2015 and 2018, i.e., two storm days and two non-storm days and the performance of the system has been compared with CODE (24- and 48-h forecast horizons).
Estimating Species-Specific Stem Size Distributions of Uneven-Aged Mixed Deciduous Forests Using ALS Data and Neural Networks
Authors: Leclère Louise , Lejeune Philippe , Bolyn Corentin , Latte Nicolas
Published: March 2022

Sustainable forest management requires accurate fine-scale description of wood resources. Stem size distribution (SSD) by species is used by foresters worldwide as a representative overview of forest structure and species composition suitable for informing management decisions at shorter and longer terms. In mixed uneven-aged deciduous forests, tree data required for SSD estimation are most often collected in the field through traditional forest management inventories (FMIs), but these are time-consuming and costly with respect to the sampled area. Combining FMIs with remote sensing methods such as airborne laser scanning (ALS), which has high potential for predicting forest structure and composition, and is becoming increasingly accessible and affordable, could provide cheaper and faster SSD data across large areas. In this study, we developed a method for estimating species-specific SSDs by combining FMIs and dual-wavelength ALS data using neural networks (NNs). The proposed method was tested and validated using 178 FMI plots within 22,000 ha of a mixed uneven-aged deciduous forest in Belgium. The forest canopy was segmented, and metrics were derived from the ALS point cloud. A NN with a custom architecture was set up to simultaneously predict the three components required to compute species-specific SSDs (species, circumference, and number of stems) at segment level. Species-specific SSDs were thereafter estimated at stand level by aggregating the estimates for the segments. A robustness test was set up using fully independent plots to thoroughly assess the method precision at stand-level on a larger area. The global Reynolds index for the species-specific SSDs was 21.2 for the training dataset and 54.0 for the independent dataset. The proposed method does not require allometric models, prior knowledge of the structure, or the predefinition of variables; it is versatile and thus potentially adaptable to other forest types having different structures and compositions.
Effusion Rates on Mt. Etna and Their Influence on Lava Flow Hazard Assessment
Authors: Zuccarello Francesco , Bilotta Giuseppe , Cappello Annalisa , Ganci Gaetana
Published: March 2022

The rate at which lava is discharged plays a key role in controlling the distance covered by lava flows from eruptive vents. We investigate the available time-averaged discharge rates (TADRs) estimated for recent flank eruptions at Mt. Etna volcano (Italy), in order to define a possible generalized effusion rate trend which is consistent with observed real data. Our analysis indicates a rapid waxing phase in which effusion rate peaks occur for between 0.5 and 29% of the total eruption time, followed by a progressive decrease in the waning phase. Three generalized curves are built by calculating the 25th, 50th and 75th percentiles values associated with the occurrence of effusion peaks, and with the slope variations of descending curves in the waning phase. The obtained curves are used as an input for the GPUFLOW model in order to perform numerical simulations of the lava flows paths on inclined planes, and are compared with those generated by using effusion rate curves with a bell-shaped time-distribution. Our tests show how these characteristic curves could impact single-vent scenarios, as well as short- and long-term hazard maps, with maximum variations of up to 40% for a specific category of eruptive events.
A Method Combining Line Detection and Semantic Segmentation for Power Line Extraction from Unmanned Aerial Vehicle Images
Authors: Zhao Wenbo , Dong Qing , Zuo Zhengli
Published: March 2022

Power line extraction is the basic task of power line inspection with unmanned aerial vehicle (UAV) images. However, due to the complex backgrounds and limited characteristics, power line extraction from images is a difficult problem. In this paper, we construct a power line data set using UAV images and classify the data according to the image clutter (IC). A method combining line detection and semantic segmentation is used. This method is divided into three steps: First, a multi-scale LSD is used to determine power line candidate regions. Then, based on the object-based Markov random field (OMRF), a weighted region adjacency graph (WRAG) is constructed using the distance and angle information of line segments to capture the complex interaction between objects, which is introduced into the Gibbs joint distribution of the label field. Meanwhile, the Gaussian mixture model is utilized to form the likelihood function by taking the spectral and texture features. Finally, a Kalman filter (KF) and the least-squares method are used to realize power line pixel tracking and fitting. Experiments are carried out on test images in the data set. Compared with common power line extraction methods, the proposed algorithm shows better performance on images with different IC. This study can provide help and guidance for power line inspection.
Land Use Quantile Regression Modeling of Fine Particulate Matter in Australia
Authors: Wu Peng , Song Yongze
Published: March 2022

Small data samples are still a critical challenge for spatial predictions. Land use regression (LUR) is a widely used model for spatial predictions with observations at a limited number of locations. Studies have demonstrated that LUR models can overcome the limitation exhibited by other spatial prediction models which usually require greater spatial densities of observations. However, the prediction accuracy and robustness of LUR models still need to be improved due to the linear regression within the LUR model. To improve LUR models, this study develops a land use quantile regression (LUQR) model for more accurate spatial predictions for small data samples. The LUQR is an integration of the LUR and quantile regression, which both have advantages in predictions with a small data set of samples. In this study, the LUQR model is applied in predicting spatial distributions of annual mean PM2.5concentrations across the Greater Sydney Region, New South Wales, Australia, with observations at 19 valid monitoring stations in 2020. Cross validation shows that the goodness-of-fit can be improved by 25.6–32.1% by LUQR models when compared with LUR, and prediction root mean squared error (RMSE) and mean absolute error (MAE) can be reduced by 10.6–13.4% and 19.4–24.7% by LUQR models, respectively. This study also indicates that LUQR is a more robust model for the spatial prediction with small data samples than LUR. Thus, LUQR has great potentials to be widely applied in spatial issues with a limited number of observations.
Cloud–Snow Confusion with MODIS Snow Products in Boreal Forest Regions
Authors: Wang Xiaoyan , Han Chao , Ouyang Zhiqi , Chen Siyong , Guo Hui , Wang Jian , Hao Xiaohua
Published: March 2022

Reliable cloud masks in Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products have a high potential to improve the retrieval of snow properties. However, cloud–snow confusion is a popular problem in MODIS snow cover products, especially in boreal forest areas. A large amount of forest snow is misclassified as clouds because of the low normalized difference snow index (NDSI), and excessive cloud masks limit the application of snow products. In addition, ice clouds are easily misclassified as snow due to their similar spectral characteristics, which leads to snow commission errors. In this paper, we quantitatively evaluated the cloud–snow confusion in Northeast China and found that snow-covered forests and transition zones from snow-covered to snow-free areas are prone to being misclassified as clouds, while clouds are less likely to be misclassified as snow. A temporal-sequence cloud–snow-distinguishing algorithm based on the high-frequency observation characteristics of the Himawarri-8 geostationary meteorological satellite is proposed. In the temporal-sequence images acquired from that satellite, the NDSI variance in cloud pixels should be greater than that of snow because clouds vary over time, while snow is relatively stable. In the MODIS snow cover products, the cloud pixels with NDSI variance lower than a threshold are identified as cloud-free areas and attributed their raw NDSI value, while the snow pixels with NDSI variance greater than the threshold are marked as clouds. We applied this method to MOD10A1 C6 in Northeast China. The results showed that the excessive cloud masks were greatly eliminated, and the new cloud mask was in good agreement with the real cloud distribution. At the same time, some possible ice clouds which had been misclassified as snow for their spectral characteristics similar to those of snow were identified correctly.
3D Distance Filter for the Autonomous Navigation of UAVs in Agricultural Scenarios
Authors: Donati Cesare , Mammarella Martina , Comba Lorenzo , Biglia Alessandro , Gay Paolo , Dabbene Fabrizio
Published: March 2022

In precision agriculture, remote sensing is an essential phase in assessing crop status and variability when considering both the spatial and the temporal dimensions. To this aim, the use of unmanned aerial vehicles (UAVs) is growing in popularity, allowing for the autonomous performance of a variety of in-field tasks which are not limited to scouting or monitoring. To enable autonomous navigation, however, a crucial capability lies in accurately locating the vehicle within the surrounding environment. This task becomes challenging in agricultural scenarios where the crops and/or the adopted trellis systems can negatively affect GPS signal reception and localisation reliability. A viable solution to this problem can be the exploitation of high-accuracy 3D maps, which provide important data regarding crop morphology, as an additional input of the UAVs’ localisation system. However, the management of such big data may be difficult in real-time applications. In this paper, an innovative 3D sensor fusion approach is proposed, which combines the data provided by onboard proprioceptive (i.e., GPS and IMU) and exteroceptive (i.e., ultrasound) sensors with the information provided by a georeferenced 3D low-complexity map. In particular, the parallel-cuts ellipsoid method is used to merge the data from the distance sensors and the 3D map. Then, the improved estimation of the UAV location is fused with the data provided by the GPS and IMU sensors, using a Kalman-based filtering scheme. The simulation results prove the efficacy of the proposed navigation approach when applied to a quadrotor that autonomously navigates between vine rows.
Forward Scatter Radar Meets Satellite: Passive Sensing of Aerial Target Using Satellite Communication Waveforms
Authors: Liu Mingqian , Zhang Zhenju , Chen Yunfei , Zheng Shifei , Ge Jianhua
Published: March 2022

The problem of single-channel reception of global positioning system (GPS) communication waveforms makes passive sensing of aerial target difficult because of forward scatter. This paper proposes a novel aerial target passive sensing method based on linear canonical transformation (LCT) using the forward scattered satellite communication waveforms. The proposed method firstly preprocesses the received signal based on the characteristics of the traditional satellite tracking loop and the forward scattered satellite communication waveforms to effectively suppress the interference of the direct wave through DC removal. Then, the Gaussian noise and multipath interference in the channel are suppressed by applying a rectangular window to its linear canonical domain. Finally, aerial target sensing is performed based on the peak value of signals in the linear canonical transform domain. The characteristic signal is constructed by analyzing the satellite communication waveforms. Combining the linear canonical transform with the matched filter (MF) to estimate the target parameter. Simulation results show that the proposed method can effectively perform the aerial target sensing by using satellite communication waveforms in the forward scatter scenario.
Habitat Classification Predictions on an Undeveloped Barrier Island Using a GIS-Based Landscape Modeling Approach
Authors: Russ Emily R. , Charbonneau Bianca R. , Altman Safra , Reif Molly K. , Swannack Todd M.
Published: March 2022

Landscape models are essential tools that link landscape patterns to ecological processes. Barrier island vegetation communities are strongly correlated with geomorphology, which makes elevation-based metrics suitable for developing a predictive habitat classification model in these systems. In this study, multinomial logistic regression is used to predict herbaceous, sparse, and woody habitat distributions on the North End of Assateague Island from slope, distance to shore, and elevation change, all of which are derived from digital elevation models (DEMs). Sparse habitats, which were generally found closest to shore in areas that are exposed to harsh conditions, had the highest predictive accuracy. Herbaceous and woody habitats occupied more protected inland settings and had lower predictive accuracies. A majority of woody cells were misclassified as herbaceous likely because of the similarity in the predictive parameter distributions. This relatively simple model is transparent and does not rely on subjective interpretations. This makes it an effective tool that can directly aid practitioners making coastal management decisions surrounding storm response planning and conservation management. The model results were used in a nutrient sequestration application to quantify carbon and nitrogen stored in barrier island vegetation. This represents an example of how the model results can be used to assign economic value of ecosystem services in a coastal system to justify different management and conservation initiatives.
Framework for Remote Sensing and Modelling of Lithium-Brine Deposit Formation
Authors: Rossi Cristian , Bateson Luke , Bayaraa Maral , Butcher Andrew , Ford Jonathan , Hughes Andrew
Published: March 2022

The demand for “green” metals such as lithium is increasing as the world works to reduce its reliance on fossil fuels. More than half of the world’s lithium resources are contained in lithium-brine deposits, including the salt flats, or “salars”, of the Andean region of South America, also known as the Lithium Triangle. The genesis of lithium-brine deposits is largely driven by the leaching of lithium from source rocks in watersheds, transport via groundwater systems to salars, and evaporative concentration in salars. The goal of this research is to create a consistent and seamless methodology for tracking lithium mass from its source in the watershed to its greatest concentration in the nucleus. The area of interest is in and around Bolivia’s Salar de Uyuni, the world’s largest salt flat. We explore how Li-brine deposits form, where the water and solute come from, how the brines are formed, and how abstraction affects the mass balance inside the salar. To support the entire system, open-source Earth observation (EO) data are analysed. We found that by constructing a flexible and repeatable workflow, the question of how lithium reaches the Salar de Uyuni can be addressed. The work demonstrated the importance of groundwater flow to the river network and highlighted the need for flow data for the main river supplying the salar with both water inflow and lithium mass.