bluuebunny/crossref_metadata_2025 huggingface dataset:
A Spike-like Self-Assembly of Polyaspartamide Integrated with Functionalized Nanoparticles
Authors: Han Sa Ra , Ahn Yujin , Cho Sungwoo , Jeong Hyewon , Ji Yoonsook , Jung Woonggyu , Jeong Jae Hyun
Published: January 2024

The integration of nanoparticles (NPs) into molecular self-assemblies has been extensively studied with the aim of building well-defined, ordered structures which exhibit advanced properties and performances. This study demonstrates a novel strategy for the preparation of a spike-like self-assembly designed to enhance UV blocking. Poly(2-hydroxyethyl aspartamide) (PHEA) substituted with octadecyl chains and menthyl anthranilate (C18-M-PHEA) was successfully synthesized by varying the number of grafted groups to control their morphology and UV absorption. The in situ incorporation of polymerized rod-like TiO2 within the C18-M-PHEA self-aggregates generated spike-like self-assemblies (TiO2@C18-M-PHEA) with a chestnut burr structure in aqueous solution. The results showed that the spike-like self-assemblies integrated with TiO2 NPs exhibited a nine-fold increase in UV protection by simultaneous UV absorption and scattering compared with the pure TiO2 NPs formed via a bulk mixing process. This work provides a novel method for UV protection using self-assembling poly(amino acid)s derivatives integrated with functional nanoparticles to tune their morphology and organization.
Efficient Regulation of the Cross-Linking Structure in Polyurethane: Achieving Outstanding Processing and Mechanical Properties for a Wind Turbine Blade
Authors: Jiang Zijin , Li Lingtong , Fu Luoping , Xiong Gaohu , Wu Hong , Guo Shaoyun
Published: January 2024

Although epoxy resin has been extensively used in the field of wind turbine blades, polyurethane has attracted much attention in recent years, due to its potential value of better fatigue resistance, lower processing viscosity and higher strength than epoxy resin blades. Herein, we construct a dense cross-linking structure in polyurethane (PU) based on different amounts of hydroxypropyl methacrylate (HPMA) with low processing viscosity and excellent mechanical properties. By increasing the content of HPMA, the thermal stability of PU is enhanced, but the micro-morphology does not change significantly. When the content of HPMA is 50 g (in 200 g copolymer), the PU sample PH-50 exhibits a viscosity of 70 MPa·s and a gelation time of 120 min at 25 °C, which is sufficient to complete processes like pouring and filling. By post-curing the PH-50 at 80 °C for 2 h, the heat distortion temperature can reach 72 °C, indicating the increase of temperature resistance. The PU copolymers also have excellent mechanical and dynamic thermo-mechanical properties due to the cross-linking structure between PU chains and poly-HPMA chains. Additionally, the PU copolymer has excellent compatibility with various glass fiber fabrics (GFF), showing a good match in the vacuum infusion experiment and great properties in the mechanical test. By compounding PH-50 with GFF, the composite with high strength is easily prepared for a wind turbine blade in various positions. The tensile strengths of the composites are all over 1000 MPa in the 0° direction. Such composites are promising for the future development of wind turbine blades that meet the stringent requirements for outstanding processing and mechanical properties.
Copolymerization of Ethylene with Functionalized 1,1-Disubstituted Olefins Using a Fluorenylamido-Ligated Titanium Catalyst
Authors: Ajala Oluwaseyi Aderemi , Ono Moeko , Nakayama Yuushou , Tanaka Ryo , Shiono Takeshi
Published: January 2024

Considering the sustainability of material development, coordination polymerization catalysts effective for 1,1-disubstituted olefins are receiving a great deal of attention because they can introduce a variety of plant-derived comonomers, such as β-pinene and limonene, into polyolefins. However, due to their sterically encumbered property, incorporating these monomers is difficult. Herein, we succeeded in the copolymerization of ethylene with various hydroxy- or siloxy-substituted vinylidenes using a fluorenylamido-ligated titanium catalyst–MMAO system. This is the first example of ethylene/polar 1,1-disubstituted olefins’ copolymerization using an early transition metal catalyst system. The polymerization proceeded at room temperature without pressurizing ethylene, and high-molecular-weight, functionalized polyethylene was obtained. The obtained copolymer showed a reduced water contact angle compared with that of the ethylene/isobutene copolymer, demonstrating the increment in hydrophilicity by hydroxy groups.
Structure–Performance Correlation Inspired Platinum-Assisted Anode with a Homogeneous Ionomer Layer for Proton Exchange Membrane Water Electrolysis
Authors: Cheng Feng , Tian Tian , Wang Rui , Zhang Hao , Zhu Liyan , Tang Haolin
Published: January 2024

PEMWE is becoming one of the most promising technologies for efficient and green hydrogen production, while the anode OER process is deeply restricted by the now commercially used iridium oxide with sluggish reaction kinetics and super high cost. Deeply exploring the essential relationship between the underlying substrate materials and the performance of PEMWE cells while simultaneously excavating new practical and convenient methods to reduce costs and increase efficiency is full of challenges. Herein, two representative kinds of iridium oxide were studied, and their performance difference in PEMWE was precisely analyzed with electrochemical techniques and physical characterization and further linked to the ionomer/catalyst compound features. A novel anode with a uniform thin ionomer coating was successfully constructed, which simultaneously optimized the ionomer/catalyst aggregates as well as electrical conductivity, resulting in significantly enhanced PEMWE performance. This rigorous qualitative analysis of the structure–performance relationship as well as effective ionomer-affinitive optimization strategies are of great significance to the development of next-generation high-performance PEM water electrolyzers.
Atmospheric Pressure Plasma Jet Exposure of Polylactic Acid Surfaces for Better Adhesion: Plasma Parameters towards Polymer Properties
Authors: Nastuta Andrei Vasile , Asandulesa Mihai , Doroftei Florica , Dascalu Ioan-Andrei , Varganici Cristian-Dragos , Tiron Vasile , Topala Ionut
Published: January 2024

Polymers play a crucial role in multiple industries; however, surface modification is necessary for certain applications. Exposure to non-thermal plasma provides a viable and environmentally beneficial option. Fused deposition molding utilizes biodegradable polylactic acid, although it encounters constraints in biomedical applications as a result of inadequate mechanical characteristics. This study investigates the effects of atmospheric pressure plasma generated by a dielectric barrier discharge system using helium and/or argon on the modification of polylactic acid surfaces, changes in their wettability properties, and alterations in their chemical composition. The plasma source was ignited in either He or Ar and was tailored to fit the best operational conditions for polymer exposure. The results demonstrated the enhanced wettability of the polymer surface following plasma treatment (up to 40% in He and 20% in Ar), with a marginal variation observed among treatments utilizing different gases. The plasma treatments also caused changes in the surface topography, morphology, roughness, and hydrophilicity. Plasma exposure also resulted in observable modifications in the dielectric characteristics, phase transition, and structure. The experimental findings endorse the utilization of plasma technologies at normal air pressure for environmentally friendly processing of polymer materials, specifically for applications that necessitate enhanced adhesion and have carefully selected prerequisites.
Aloe vera/Chitosan-Based Edible Film with Enhanced Antioxidant, Antimicrobial, Thermal, and Barrier Properties for Sustainable Food Preservation
Authors: Kaur Navjot , Somasundram Chandran , Razali Zuliana , Mourad Abdel-Hamid I. , Hamed Fathalla , Ahmed Zienab F. R.
Published: January 2024

Food bioactive packaging has received increasing attention from consumers and the food industry for its potential to reduce food waste and environmental issues. Several materials can be used to produce edible films/coats; however, bio-based, cost-effective, and sustainable coatings have gained a high reputation these days. For instance, Aloe vera gel (AV) is a promising bio-based material for edible coatings and films; therefore, the present study aimed to investigate the film-forming abilities of AV and Chitosan (CH) combination as a potential active food packaging material. The physicochemical and mechanical characteristics of formed films of various combinations were prepared at different concentrations, i.e., CH (0.5% w/v), AV (100%), CH:AV (75:25), and CH:AV (60:40). The results showed significant differences among all the prepared edible films wherein these differences were mainly on account of incorporating AV gel. The rheological and antioxidant properties of the formulations improved with the inclusion of AV gel. The films composed of CH:AV (60:40) positively affected the water solubility, thermal properties, and water vapour permeability of the edible films. The X-ray Diffraction (XRD) and Scanning electron microscopy (SEM) results showed that the films composed of CH:AV, (60:40) were amorphous and had smooth morphology. Further, the edible film solutions were applied to fresh figs (Ficus carica) to investigate their role in preserving fruits during storage. A significant reduction in microbial growth was found in coated fruits after 28 days of cold storage. The films composed of CH and AV showed overall improved results compared to the CH (0.5%, w/v). Therefore, the used formulations (CH:AV, 60:40) can form a sustainable film that has the potential to be utilized for fresh product preservation to maintain its quality and shelf life.
Catalyst-Free Amino-Yne Click Reaction: An Efficient Way for Immobilizing Amoxicillin onto Polymeric Surfaces
Authors: Sánchez-Bodón Julia , Diaz-Galbarriatu Maria , Sola-Llano Rebeca , Ruiz-Rubio Leire , Vilas-Vilela José Luis , Moreno-Benitez Isabel
Published: January 2024

Surface modifications play a crucial role in enhancing the functionality of biomaterials. Different approaches can be followed in order to achieve the bioconjugation of drugs and biological compounds onto polymer surfaces. In this study, we focused on the immobilization of an amoxicillin antibiotic onto the surface of poly-L-lactic acid (PLLA) using a copper-free amino-yne click reaction. The utilization of this reaction allowed for a selective and efficient bioconjugation of the amoxicillin moiety onto the PLLA surface, avoiding copper-related concerns and ensuring biocompatibility. The process involved sequential steps that included surface activation via alkaline hydrolysis followed by an amidation reaction with ethylendiamine, functionalization with propiolic groups, and subsequent conjugation with amoxicillin via a click chemistry approach. Previous amoxicillin immobilization using tryptophan and fluorescent amino acid conjugation was carried out in order to determine the efficacy of the proposed methodology. Characterization techniques such as X-ray photoelectron spectroscopy (XPS), Attenuated Total Reflection (ATR)–Fourier Transform Infrared (FTIR) spectroscopy, surface imaging, water contact angle determination, and spectroscopic analysis confirmed the successful immobilization of both tryptophan and amoxicillin while maintaining the integrity of the PLLA surface. This tailored modification not only exhibited a novel method for surface functionalization but also opens avenues for developing antimicrobial biomaterials with improved drug-loading capacity.
Specifics of Cryopreservation of Hydrogel Biopolymer Scaffolds with Encapsulated Mesenchymal Stem Cells
Authors: Egorikhina Marfa N. , Rubtsova Yulia P. , Linkova Daria D. , Charykova Irina N. , Farafontova Ekaterina A. , Aleinik Diana Ya.
Published: January 2024

The demand for regenerative medicine products is growing rapidly in clinical practice. Unfortunately, their use has certain limitations. One of these, which significantly constrains the widespread distribution and commercialization of such materials, is their short life span. For products containing suspensions of cells, this issue can be solved by using cryopreservation. However, this approach is rarely used for multicomponent tissue-engineered products due to the complexity of selecting appropriate cryopreservation protocols and the lack of established criteria for assessing the quality of such products once defrosted. Our research is aimed at developing a cryopreservation protocol for an original hydrogel scaffold with encapsulated MSCs and developing a set of criteria for assessing the quality of their functional activity in vitro. The scaffolds were frozen using two alternative types of cryocontainers and stored at either −40 °C or −80 °C. After cryopreservation, the external state of the scaffolds was evaluated in addition to recording the cell viability, visible changes during subsequent cultivation, and any alterations in proliferative and secretory activity. These observations were compared to those of scaffolds cultivated without cryopreservation. It was shown that cryopreservation at −80 °C in an appropriate type of cryocontainer was optimal for the hydrogels/adipose-derived stem cells (ASCs) tested if it provided a smooth temperature decrease during freezing over a period of at least three hours until the target values of the cryopreservation temperature regimen were reached. It was shown that evaluating a set of indicators, including the viability, the morphology, and the proliferative and secretory activity of the cells, enables the characterization of the quality of a tissue-engineered construct after its withdrawal from cryopreservation, as well as indicating the effectiveness of the cryopreservation protocol.
Collagen Matrix to Restore the Tympanic Membrane: Developing a Novel Platform to Treat Perforations
Authors: Svistushkin Mikhail , Kotova Svetlana , Zolotova Anna , Fayzullin Alexey , Antoshin Artem , Serejnikova Natalia , Shekhter Anatoly , Voloshin Sergei , Giliazova Aliia , Istranova Elena , Nikiforova Galina , Khlytina Arina , Shevchik Elena , Nikiforova Anna , Selezneva Liliya , Shpichka Anastasia , Timashev Peter S.
Published: January 2024

Modern otology faces challenges in treating tympanic membrane (TM) perforations. Instead of surgical intervention, alternative treatments using biomaterials are emerging. Recently, we developed a robust collagen membrane using semipermeable barrier-assisted electrophoretic deposition (SBA-EPD). In this study, a collagen graft shaped like a sponge through SBA-EPD was used to treat acute and chronic TM perforations in a chinchilla model. A total of 24 ears from 12 adult male chinchillas were used in the study. They were organized into four groups. The first two groups had acute TM perforations and the last two had chronic TM perforations. We used the first and third groups as controls, meaning they did not receive the implant treatment. The second and fourth groups, however, were treated with the collagen graft implant. Otoscopic assessments were conducted on days 14 and 35, with histological evaluations and TM vibrational studies performed on day 35. The groups treated with the collagen graft showed fewer inflammatory changes, improved structural recovery, and nearly normal TM vibrational properties compared to the controls. The porous collagen scaffold successfully enhanced TM regeneration, showing high biocompatibility and biodegradation potential. These findings could pave the way for clinical trials and present a new approach for treating TM perforations.
The Impact of Discrete Element Method Parameters on Realistic Representation of Spherical Particles in a Packed Bed
Authors: Ghasemi Monfared Zahra , Hellström J. Gunnar I. , Umeki Kentaro
Published: January 2024

Packed bed reactors play a crucial role in various industrial applications. This paper utilizes the Discrete Element Method (DEM), an efficient numerical technique for simulating the behavior of packed beds of particles as discrete phases. The focus is on generating densely packed particle beds. To ensure the model accuracy, specific DEM parameters were studied, including sub-step and rolling resistance. The analysis of the packed bed model extended to a detailed exploration of void fraction distribution along radial and vertical directions, considering the impact of wall interactions. Three different samples, spanning particle sizes from 0.3 mm to 6 mm, were used. Results indicated that the number of sub-steps significantly influences void fraction precision, a key criterion for comparing simulations with experimental results. Additionally, the study found that both loosely and densely packed beds of particles could be accurately represented by incorporating appropriate values for rolling friction. This value serves as an indicator of both inter-particle friction and friction between particles and the walls. An optimal rolling friction coefficient has been thereby suggested for the precise representation for the densely packed bed of spherical char particles.
Research on Pump-Controlled AGC Micro-Displacement Position Control of Lithium Battery Pole Strip Mill Based on Friction Compensation Control Strategy of Imoroved LuGre Pattern
Authors: Wang Kai , Chen Gexin , Liu Keyi , Wang Fei , Wang Meng , Zhang Tiangui
Published: January 2024

Accurate mathematical patterning of friction has always been a significant research project in the domains of machinery and control, and has played a crucial role in the analysis, control and compensation of mechanical systems containing friction. For high-property electrohydraulic servo control systems, friction compensation is an urgent problem to be solved. The LuGre friction pattern can represent most frictional behaviors, but the LuGre friction pattern is piecewise-continuous, making it non-differentiable. Therefore, the question of how to combine the LuGre friction pattern, enhancing its tracking capacity and robust performance problem, to friction perturbation in hydraulic backstep devices is an important focus for research. In this study, the conventional LuGre friction pattern was enhanced using the continuous differentiability of a friction of rest pattern that laid the foundation of a smooth tangent function. Laying the foundation of an electrohydraulic servo pump-controlled hydraulic roll-gap thickness automatic control system (pump-controlled AGC) pattern, a self-adapting friction compensation controller laid the foundation of the enhanced LuGre pattern. The gradual tracking capacity was determined academically using conditions of parameter, uncertainty and nonlinear friction, and the position control precision of the pump-controlled AGC system was enhanced. The steady-state error of the self-adapting friction compensation control system, which laid the foundation of the enhanced LuGre pattern, attained ±0.1 μm, and the tracking capacity was better than the LuGre pattern control and the conventional PID control strategy at low input speed.
Adsorption Performance and Mechanism of Fe(II) Adsorption in Abandoned Mine Water of Nonstick Coal
Authors: Shi Zhuolin , Wu Chengle , Wang Furong , Sun Jialong , Xu Yingnan , Shen Jinhang
Published: January 2024

Aiming at the problem of the low reuse rate of mine water due to the high content of heavy metals in mine water, in this research, the microcharacterization means of EDX, XRD, BET, SEM, and FT-IR were used to characterize the nonstick coal in a mine in western China. The effects of solid–liquid ratio, solution pH, solution temperature, adsorption time, and initial concentration of the solution on the adsorption of Fe(II) by the nonstick coal were analyzed. The adsorption performance of nonstick coal on adsorbed Fe(II) was analyzed under different influencing factors. The results showed that the adsorption capacity and unit removal rate of the coal samples gradually decreased with the increase in the solid–liquid ratio; the adsorption amount increased with the increase in pH in an “S” shape, and the adsorption effect was better in the range of pH = 5~7; and the adsorption amount increased linearly with the temperature. The quasi-secondary kinetic model and Langmuir model could fit the adsorption kinetic curve and isothermal adsorption curve better, which indicated that the adsorption of Fe(II) by the nonstick coal was dominated by the chemical adsorption of the monomolecular layer. The quantitative analysis of the FT-IR results showed that the adsorption of Fe(II) was mainly by complexation with -OH detached from the coal samples to produce precipitation.
Comparison of the Work of Wastewater Treatment Plant “Ravda” in Summer and Winter Influenced by the Seasonal Mass Tourism Industry and COVID-19
Authors: Bogdanova Magdalena , Yotinov Ivaylo , Topalova Yana
Published: January 2024

Mass tourism puts enormous pressure on wastewater treatment plants due to its expansive growth during the summer months. To adapt to the fluctuations, the Ravda wastewater treatment plant (WWTP) uses innovative methods and technologies, allowing for “shrinking” and “expanding” of the facilities according to the season. This has been built in stages over the years, with two separate biological treatment lines adapting to different numbers of tourists and to the quantity of influent wastewater. The aim of this study is to make a comparative assessment of the work of WWTP Ravda in the summer and winter seasons and its effectiveness, as well as to compare them. In addition, it examines the years of the COVID-19 pandemic, when a much higher consumption of water per person was noted. Data were analyzed for the period of 2018–2022 inclusive, comparing influent and effluent BOD5 and COD in the summer and winter. Nitrogen and phosphorus removal efficiencies were also tracked. The study shows that municipal wastewater treatment is effective, but much higher values, close to the maximum permissible discharge values, are observed during the tourist season. With the continued growth of the tourism sector, the Ravda wastewater treatment plant would not be able to cope with the discharge standards set by the Ministry of Environment and Water, so measures need to be taken promptly.
Comparison of Trenchless and Excavation Technologies in the Restoration of a Sewage Network and Their Carbon Footprints
Authors: Chorazy Tomáš , Hlavínek Petr , Raček Jakub , Pietrucha-Urbanik Katarzyna , Tchórzewska-Cieślak Barbara , Keprdová Šárka , Dufek Zdeněk
Published: January 2024

The restoration of aging sewer networks is a fundamental remediation approach with the aim of renewing or improving existing systems. Remediation methods include repair, renovation, and replacement (renewal). The restoration of a sewer network itself can be performed using either excavation or trenchless technologies. While these technologies offer various advantages, they also present disadvantages. The choice of a restoration technology depends on numerous parameters, including economic factors and local conditions (such as the construction of the existing sewage network, available working space, traffic load, and environmental safety restrictions). In addition to the parameters influencing the choice of restoration technology, recent considerations have been given to constraints related to greenhouse gas emissions and the corresponding carbon footprint. Carbon footprint serves as an indicator of the restoration activity’s dependence on fossil fuels, both during implementation and operation. In the 21st century, concerns regarding carbon footprints have rapidly escalated. The reduction in carbon footprints is a crucial objective from both an economic and an ecological point of view. This article specifically addresses the prospects of monitoring the carbon footprint concerning the partial restoration of a sewer network within the historical core of the city of Brno, located in the Czech Republic. This aspect constitutes the unique and innovative contribution of the paper. The intensity of the energy demand of excavation and trenchless technologies is utilized as a direct measure of the carbon footprint of each technology. The comparative assessment demonstrates that the trenchless technology used achieves a reduction of 59.2% in CO2 emissions compared to the excavation technology. The carbon footprint of Variant 1 (trenchless technology) is 9.91 t CO2 eq., while the carbon footprint of Variant 2 (excavation technology) is 24.29 t CO2 eq. The restoration of open pipelines produces more emissions due to the higher energy consumption, making it more expensive in terms of fuel costs, waste disposal costs, and the corresponding environmental hazards.
The Moderating Role of Corporate Governance in the Relationship between Leverage and Firm Value: Evidence from the Korean Market
Authors: Tulcanaza-Prieto Ana Belén , Lee Younghwan , Anzules-Falcones Wendy
Published: January 2024

This study examines the moderating function of corporate governance (CG) to the relationship between leverage and firm value (FV) using Korean market data. The study employs ordinary least-squares panel data regressions and two methods to manage endogeneity problems. The findings show a meaningful negative relationship between leverage and FV. This relationship, however, disappears, when the interaction variable of leverage × CG is included in the econometric model. These results indicate that an effective CG mechanism may lessen the probability of either the entrenched management-decision-making behavior or the agency costs of debt and, therefore, the negative effect of debt to FV diminishes. Moreover, our data show that the relationship between leverage and FV becomes positive, even though insignificant, for firms with a high level of CG, whereas it stays significantly negative for firms with a low level of CG. We also find that leverage for firms with a high level of CG is lower than those firms with a low level of CG. These additional findings support our conclusion of the moderating role of CG, which also influences the firms’ risk, leverage, and FV. The authors recommend the implementation of a robust CG plan to decrease the information asymmetry and the agency leverage problem.
Estimation of Earth Rotation Parameters Based on BDS-3 and Discontinuous VLBI Observations
Authors: Wang Chenxiang , Sang Jizhang , Li Xingxing , Zhang Pengfei
Published: January 2024

Earth rotation parameters (ERPs) are fundamental to geodetic and astronomical studies. With its high measurement accuracy and stability, the Very Long Baseline Interferometry (VLBI) plays an irreplaceable role in estimating the ERPs and maintaining the earth reference frame. However, the imperfect global station distribution, observation discontinuity, and vast cost of the VLBI make the GNSS a more attractive technique. In 2020, the third generation of the BeiDou Navigation System (BDS), namely BDS-3, was constructed completely. In this study, we conducted a series of experiments to estimate Earth’s rotation parameters based on the continuous BDS-3 observation data, the discontinuous VLBI observation data, and the combined BDS-3 and discontinuous VLBI observation data. We used two methods, namely the weighted averaging method and the normal equation combination method, to obtain ERP combination solutions. The results are compared with the International Earth Rotation and Reference Systems Service (IERS) EOP 20C04 at 00:00:00 UTC. Final results show that (a) the estimation accuracy becomes stable when the number of BDS-3 tracking stations is more than 40. At the same time, both the number of stations and the volume of polyhedrons formed by the observing stations affect the accuracy of the ERPs estimated by the BDS-3 or VLBI. (b) Results have also shown that the inclusion of the BDS-3 IGSO and GEO satellites contributes little to the ERP estimation. (c) For the BDS-3-only MEO satellites solution, the root mean square (RMS) was 113.2 µas, 102.8 µas, and 13.1 µs/day for X-pole coordinate, Y-pole coordinate, and length of day (LOD), respectively. For the VLBI solution, the RMSs of the X-pole, Y-pole, and LOD were 100.4 µas for the X-pole, 94.2 µas for the Y-pole, and 14.1 µs/day. The RMS was 82.6 µas, 70.3 µas, and 10.5 µs/day for the combined X-pole, Y-pole, and LOD using the weighted averaging method. It was 78.2 µas, 62.6 µas, and 8.6 µs/day when the normal equation combination method was applied. This demonstrates that by taking advantage of the BDS-3 and VLBI technique combinations, accuracy in estimating the ERPs can be improved over that using either of them, in addition to enhanced stability and reliability.
Overcoming Common Pitfalls to Improve the Accuracy of Crop Residue Burning Measurement Based on Remote Sensing Data
Authors: Walker Kendra
Published: January 2024

Crop residue burning (CRB) is a major source of air pollution in many parts of the world, especially Asia. Policymakers, practitioners, and researchers have invested in measuring the extent and impacts of burning and developing interventions to reduce its occurrence. However, any attempt to measure burning, in terms of its extent, impact, or the effectiveness of interventions to reduce it, requires data on where burning occurs. These data are challenging to collect in the field, both in terms of cost and feasibility, because crop-residue fires are short-lived, each covers only a small area, and evidence of burning disappears once fields are tilled. Remote sensing offers a way to observe fields without the complications of on-the-ground monitoring. However, the same features that make CRB hard to observe on the ground also make remote-sensing-based measurements prone to inaccuracies. The extent of crop burning is generally underestimated due to missing observations, while individual plots are often falsely identified as burned due to the local dominance of the practice, a lack of training data on tilled vs. burned plots, and a weak signal-to-noise ratio that makes it difficult to distinguish between the two states. Here, we summarize the current literature on the measurement of CRB and flag five common pitfalls that hinder analyses of CRB with remotely sensed data: inadequate spatial resolution, inadequate temporal resolution, ill-fitted signals, improper comparison groups, and inadequate accuracy assessment. We take advantage of data from ground-based monitoring of CRB in Punjab, India, to calibrate and validate analyses with PlanetScope and Sentinel-2 imagery and illuminate each of these pitfalls. We provide tools to assist others in planning and conducting remote sensing analyses of CRB and stress the need for rigorous validation.
A Multi-Dimensional Feature Fusion Recognition Method for Space Infrared Dim Targets Based on Fuzzy Comprehensive with Spatio-Temporal Correlation
Authors: Zhang Shenghao , Rao Peng , Hu Tingliang , Chen Xin , Xia Hui
Published: January 2024

Space infrared (IR) target recognition has always been a key issue in the field of space technology. The imaging distance is long, the target is weak, and the feature discrimination is low, making it difficult to distinguish between high-threat targets and decoys. However, most existing methods ignore the fuzziness of multi-dimensional features, and their performance mainly depends on the accuracy of feature extraction, with certain limitations in handling uncertainty and noise. This article proposes a space IR dim target fusion recognition method, which is based on fuzzy comprehensive of spatio-temporal correlation. First, we obtained multi-dimensional IR features of the target through multi-time and multi-spectral detectors, then we established and calculated the adaptive fuzzy-membership function of the features. Next, we applied the entropy weight method to ascertain the objective fusion weights of each feature and computed the spatially fuzzified fusion judgments for the targets. Finally, the fuzzy comprehensive function was used to perform temporal recursive judgment, and the ultimate fusion recognition result was obtained by integrating the results of each temporal recursive judgment. The simulation and comparative experimental results indicate that the proposed method improved the accuracy and robustness of IR dim target recognition in complex environments. Under ideal conditions, it can achieve an accuracy of 88.0% and a recall of 97.5% for the real target. In addition, this article also analyzes the impact of fusion feature combinations, fusion frame counts, different feature extraction errors, and feature database size on recognition performance. The research in this article can enable space-based IR detection systems to make more accurate and stable decisions, promoting defense capabilities and ensuring space security.
Identification of Lunar Craters in the Chang’e-5 Landing Region Based on Kaguya TC Morning Map
Authors: Liu Yanshuang , Lai Jialong , Xie Minggang , Zhao Jiannan , Zou Chen , Liu Chaofei , Qian Yiqing , Deng Jiahao
Published: January 2024

Impact craters are extensively researched geological features that contribute to various aspects of lunar science, such as evaluating the model age, regolith thickness, etc. The method for identifying impact craters has gradually transitioned from manual counting to automated identification. Automatic crater detection based on the digital elevation model (DEM) is commonly used to detect larger craters. However, using only DEM has limitations in discerning smaller craters (diameter < ~1 km). This study utilizes an improved Faster R-CNN algorithm and the Kaguya Terrain Camera (TC) morning map to detect small impact craters in the Chang’e-5 (CE-5) landing site. It uses model fusion to improve the precision of small crater identification. The results show a recall rate of 96.33% and a precision value of 90.19% for craters with diameters exceeding 200 m. The model found a total of 187,101 impact craters in the CE-5 region. The spatial distribution density of impact craters with diameters ranging from 100 m to 200 m is approximately 2.5706/km2. For craters with diameters ranging from 200 m to 1 km, the average spatial distribution density is about 0.9016/km2. By the unbiased impact crater density of chronological analysis, the model age of the Im2 and Em4 geological units in the CE-5 region is 3.78 Ga and 2.07 Ga, respectively.
Edge IoT Prototyping Using Model-Driven Representations: A Use Case for Smart Agriculture
Authors: Guevara Ivan , Ryan Stephen , Singh Amandeep , Brandon Colm , Margaria Tiziana
Published: January 2024

Industry 4.0 is positioned at the junction of different disciplines, aiming to re-engineer processes and improve effectiveness and efficiency. It is taking over many industries whose traditional practices are being disrupted by advances in technology and inter-connectivity. In this context, enhanced agriculture systems incorporate new components that are capable of generating better decision making (humidity/temperature/soil sensors, drones for plague detection, smart irrigation, etc.) and also include novel processes for crop control (reproducible environmental conditions, proven strategies for water stress, etc.). At the same time, advances in model-driven development (MDD) simplify software development by introducing domain-specific abstractions of the code that makes application development feasible for domain experts who cannot code. XMDD (eXtreme MDD) makes this way to assemble software even more user-friendly and enables application domain experts who are not programmers to create complex solutions in a more straightforward way. Key to this approach is the introduction of high-level representations of domain-specific functionalities (called SIBs, service-independent building blocks) that encapsulate the programming code and their organisation in reusable libraries, and they are made available in the application development environment. This way, new domain-specific abstractions of the code become easily comprehensible and composable by domain experts. In this paper, we apply these concepts to a smart agriculture solution, producing a proof of concept for the new methodology in this application domain to be used as a portable demonstrator for MDD in IoT and agriculture in the Confirm Research Centre for Smart Manufacturing. Together with model-driven development tools, we leverage here the capabilities of the Nordic Thingy:53 as a multi-protocol IoT prototyping platform. It is an advanced sensing device that handles the data collection and distribution for decision making in the context of the agricultural system and supports edge computing. We demonstrate the importance of high-level abstraction when adopting a complex software development cycle within a multilayered heterogeneous IT ecosystem.
Measurement Modeling and Performance Analysis of a Bionic Polarimetric Imaging Navigation Sensor Using Rayleigh Scattering to Generate Scattered Sunlight
Authors: Wan Zhenhua , Zhao Kaichun , Cheng Haoyuan , Fu Peng
Published: January 2024

The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design.
Data-Driven Structural Health Monitoring: Leveraging Amplitude-Aware Permutation Entropy of Time Series Model Residuals for Nonlinear Damage Diagnosis
Authors: Zhang Xuan , Li Luyu , Qu Gaoqiang
Published: January 2024

In structural health monitoring (SHM), most current methods and techniques are based on the assumption of linear models and linear damage. However, the damage in real engineering structures is more characterized by nonlinear behavior, including the appearance of cracks and the loosening of bolts. To solve the structural nonlinear damage diagnosis problem more effectively, this study combines the autoregressive (AR) model and amplitude-aware permutation entropy (AAPE) to propose a data-driven damage detection method. First, an AR model is built for the acceleration data from each structure sensor in the baseline state, including determining the model order using a modified iterative method based on the Bayesian information criterion (BIC) and calculating the model coefficients. Subsequently, in the testing phase, the residuals of the AR model are extracted as damage-sensitive features (DSFs), and the AAPE is calculated as a damage classifier to diagnose the nonlinear damage. Numerical simulation of a six-story building model and experimental data from a three-story frame structure at the Los Alamos Laboratory are utilized to illustrate the effectiveness of the proposed methodology. In addition, to demonstrate the advantages of the present method, we analyzed AAPE in comparison with other advanced univariate damage classifiers. The numerical and experimental results demonstrate the proposed method’s advantages in detecting and localizing minor damage. Moreover, this method is applicable to distributed sensor monitoring systems.
GNSS Radio Frequency Interference Monitoring from LEO Satellites: An In-Laboratory Prototype
Authors: Troglia Gamba Micaela , Polidori Brendan David , Minetto Alex , Dovis Fabio , Banfi Emilio , Dominici Fabrizio
Published: January 2024

The disruptive effect of radio frequency interference (RFI) on global navigation satellite system (GNSS) signals is well known, and in the last four decades, many have been investigated as countermeasures. Recently, low-Earth orbit (LEO) satellites have been looked at as a good opportunity for GNSS RFI monitoring, and the last five years have seen the proliferation of many commercial and academic initiatives. In this context, this paper proposes a new spaceborne system to detect, classify, and localize terrestrial GNSS RFI signals, particularly jamming and spoofing, for civil use. This paper presents the implementation of the RFI detection software module to be hosted on a nanosatellite. The whole development work is described, including the selection of both the target platform and the algorithms, the implementation, the detection performance evaluation, and the computational load analysis. Two are the implemented RFI detectors: the chi-square goodness-of-fit (GoF) algorithm for non-GNSS-like interference, e.g., chirp jamming, and the snapshot acquisition for GNSS-like interference, e.g., spoofing. Preliminary testing results in the presence of jamming and spoofing signals reveal promising detection capability in terms of sensitivity and highlight room to optimize the computational load, particularly for the snapshot-acquisition-based RFI detector.
Self-Interested Coalitional Crowdsensing for Multi-Agent Interactive Environment Monitoring
Authors: Liu Xiuwen , Lei Xinghua , Li Xin , Chen Sirui
Published: January 2024

As a promising paradigm, mobile crowdsensing (MCS) takes advantage of sensing abilities and cooperates with multi-agent reinforcement learning technologies to provide services for users in large sensing areas, such as smart transportation, environment monitoring, etc. In most cases, strategy training for multi-agent reinforcement learning requires substantial interaction with the sensing environment, which results in unaffordable costs. Thus, environment reconstruction via extraction of the causal effect model from past data is an effective way to smoothly accomplish environment monitoring. However, the sensing environment is often so complex that the observable and unobservable data collected are sparse and heterogeneous, affecting the accuracy of the reconstruction. In this paper, we focus on developing a robust multi-agent environment monitoring framework, called self-interested coalitional crowdsensing for multi-agent interactive environment monitoring (SCC-MIE), including environment reconstruction and worker selection. In SCC-MIE, we start from a multi-agent generative adversarial imitation learning framework to introduce a new self-interested coalitional learning strategy, which forges cooperation between a reconstructor and a discriminator to learn the sensing environment together with the hidden confounder while providing interpretability on the results of environment monitoring. Based on this, we utilize the secretary problem to select suitable workers to collect data for accurate environment monitoring in a real-time manner. It is shown that SCC-MIE realizes a significant performance improvement in environment monitoring compared to the existing models.
Viewer Engagement in Response to Mixed and Uniform Emotional Content in Marketing Videos—An Electroencephalographic Study
Authors: Rejer Izabela , Jankowski Jarosław , Dreger Justyna , Lorenz Krzysztof
Published: January 2024

This study presents the results of an experiment designed to investigate whether marketing videos containing mixed emotional content can sustain consumers interest longer compared to videos conveying a consistent emotional message. During the experiment, thirteen participants, wearing EEG (electroencephalographic) caps, were exposed to eight marketing videos with diverse emotional tones. Participant engagement was measured with an engagement index, a metric derived from the power of brain activity recorded over the frontal and parietal cortex and computed within three distinct frequency bands: theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz). The outcomes indicated a statistically significant influence of emotional content type (mixed vs. consistent) on the duration of user engagement. Videos containing a mixed emotional message were notably more effective in sustaining user engagement, whereas the engagement level for videos with a consistent emotional message declined over time. The principal inference drawn from the study is that advertising materials conveying a consistent emotional message should be notably briefer than those featuring a mixed emotional message to achieve an equivalent level of message effectiveness, measured through engagement duration.
Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring
Authors: Silberstein Jonathan , Wellbrook Matthew , Hannigan Michael
Published: January 2024

The use of low-cost sensors (LCSs) for the mobile monitoring of oil and gas emissions is an understudied application of low-cost air quality monitoring devices. To assess the efficacy of low-cost sensors as a screening tool for the mobile monitoring of fugitive methane emissions stemming from well sites in eastern Colorado, we colocated an array of low-cost sensors (XPOD) with a reference grade methane monitor (Aeris Ultra) on a mobile monitoring vehicle from 15 August through 27 September 2023. Fitting our low-cost sensor data with a bootstrap and aggregated random forest model, we found a high correlation between the reference and XPOD CH4 concentrations (r = 0.719) and a low experimental error (RMSD = 0.3673 ppm). Other calibration models, including multilinear regression and artificial neural networks (ANN), were either unable to distinguish individual methane spikes above baseline or had a significantly elevated error (RMSDANN = 0.4669 ppm) when compared to the random forest model. Using out-of-bag predictor permutations, we found that sensors that showed the highest correlation with methane displayed the greatest significance in our random forest model. As we reduced the percentage of colocation data employed in the random forest model, errors did not significantly increase until a specific threshold (50 percent of total calibration data). Using a peakfinding algorithm, we found that our model was able to predict 80 percent of methane spikes above 2.5 ppm throughout the duration of our field campaign, with a false response rate of 35 percent.
Variational Optimization for Sustainable Massive MIMO Base Station Switching
Authors: Al-Samawi Aida , Nissirat Liyth
Published: January 2024

Massive MIMO networks are a promising technology for achieving ultra-high capacity and meeting future wireless service demand. Massive MIMO networks, on the other hand, consume intensive energy. As a result, energy-efficient operation of massive MMO networks became a requirement rather than a luxury. Many NP-hard concavity search algorithms for optimal base station switching on-off scheme have been developed. This paper demonstrates the formulation of massive MIMO networks energy efficiency as a constrained variational problem. Our proposed method solution’s uniqueness and boundedness are demonstrated and proven. The developed system is a total energy optimization problem formulation. Furthermore, the order in which the base stations are switched on and off is specified for minimal handover overhead signaling and fair user capacity sharing. Results showed that variational optimization yielded optimal base station switching on and off with considerable energy saving achieved and maintaining the user capacity demand. Moreover, the proposed base station selection criteria provided suboptimal handover overhead signaling.