bluuebunny/crossref_metadata_2025 huggingface dataset:
Phase-Shift Laser Ranging Technology Based on Multi-Frequency Carrier Phase Modulation
Authors: Zhou Lisha , He Hongyu , Sun Jianfeng , Lin Baojun
Published: August 2022

Compared to traditional phase laser ranging technology, phase-shift laser ranging technology based on carrier phase modulation has significant advantages, such as simple modulation and demodulation, as well as simultaneous ranging and velocity measurements with high precision. To expand the range and ensure the ranging precision in carrier phase modulation in phase-shift laser ranging technology, we propose a phase-shift laser ranging system based on multi-frequency carrier phase modulation. We analyzed the effects of the stagger coefficient, modulation depth, and signal-to-noise ratio on the ranging precision by simulation. Finally, we built an experimental system with a range of 300 m by choosing appropriate parameters and conducting linearity and range precision tests. The experimental results show that the system has good linearity, and the ranging precision can reach 1 cm when the signal-to-noise ratio is 20 dB.
Plant-Endophyte Interaction during Biotic Stress Management
Authors: Pathak Parul , Rai Vineet Kumar , Can Hasan , Singh Sandeep Kumar , Kumar Dharmendra , Bhardwaj Nikunj , Roychowdhury Rajib , de Azevedo Lucas Carvalho Basilio , Kaushalendra  , Verma Hariom , Kumar Ajay
Published: August 2022

Plants interact with diverse microbial communities and share complex relationships with each other. The intimate association between microbes and their host mutually benefit each other and provide stability against various biotic and abiotic stresses to plants. Endophytes are heterogeneous groups of microbes that live inside the host tissue without showing any apparent sign of infection. However, their functional attributes such as nutrient acquisition, phytohormone modulation, synthesis of bioactive compounds, and antioxidant enzymes of endophytes are similar to the other rhizospheric microorganisms. Nevertheless, their higher colonization efficacy and stability against abiotic stress make them superior to other microorganisms. In recent studies, the potential role of endophytes in bioprospecting has been broadly reported. However, the molecular aspect of host–endophyte interactions is still unclear. In this study, we have briefly discussed the endophyte biology, colonization efficacy and diversity pattern of endophytes. In addition, it also summarizes the molecular aspect of plant–endophyte interaction in biotic stress management.
Biodegradable Polymers-Based Smart Nanocrystals for Loxoprofen Delivery with Enhanced Solubility: Design, Fabrication and Physical Characterizations
Authors: Khan Barkat Ali , Khalid Hina , Khan Muhammad Khalid , Hosny Khaled M. , Khan Shahzeb , Rizg Waleed Y. , Safhi Awaji Y. , Halwani Abdulrahman A. , Almehmady Alshaimaa M. , Menaa Farid
Published: August 2022

Nanocrystals are carrier-free, submicron-sized, colloidal drug delivery systems with particle sizes in the mean nanometer range. Nanocrystals have high bioavailability and fast absorption because of their high dissolution velocity and enhanced adhesiveness to cell membranes. Loxoprofen, a nonsteroidal anti-inflammatory drug belonging to the Biopharmaceutical Classification System (BCS) II drug class, was selected as the model drug. The aim of this study was to formulate nanocrystals of loxoprofen. A total of 12 formulations (F1 to F12) were prepared. An antisolvent technique was used to determine the effects of various stabilizers and processing conditions on the optimization of formulations. The various stabilizers used were hydroxypropyl methylcellulose (0.5%), polyvinylpyrrolidone (0.5%), and sodium lauryl sulfate (0.1%). The various characterizations conducted for this research included stability studies at 25 °C and 4 °C, scanning electron microscopy, transmission electron microscopy (TEM), X-ray powder diffraction (XRPD), differential scanning calorimetry (DSC), zeta potentials, polydispersity indexes, and dissolution studies. F10 was the optimized formulation that showed stability at room temperature, as well as at a refrigerated temperature, for 30 days. A high dissolution rate (100% within the first 10 min) was shown by comparative dissolution studies of nano-suspensions with the micro-suspension and raw loxoprofen. F10 formulation had a non-porous and crystalline morphology on evaluation by TEM and XRPD, respectively, and the average particle size was 300 ± 0.3 nm as confirmed by TEM. DSC recorded a reduction in the melting point (180 °C processed and 200 °C unprocessed melting points). The dissolution rate and solubility of the formulated loxoprofen nanocrystals were significantly enhanced. It can be concluded that selecting suitable stabilizers (i.e., polymers and surfactants) can produce stable nanocrystals, and this can potentially lead to a scaling up of the process for commercialization.
Evaluation of Fatigue Life of Recycled Opaque PET from Household Milk Bottle Wastes
Authors: Korycki Adrian , Garnier Christian , Irusta Silvia , Chabert France
Published: August 2022

Polyethylene terephthalate (PET) is among the most used thermoplastic polymers in large scale manufacturing. Opaque PET is increasingly used in milk bottles to save weight and to bring a glossy white aspect due to TiO2 nanoparticles. The recyclability of opaque PET is an issue: whereas the recycling channels are well established for transparent PET, the presence of opaque PET in household wastes weakens those channels: opaque bottles cannot be mixed with transparent ones because the resulting blend is not transparent anymore. Many research efforts focus on the possibility to turn opaque PET into resources, as one key to a more circular economy. A recent study has demonstrated the improvement of the mechanical properties of recycled PET through reactive extrusion. In the present work, the lifespan of recycled opaque PET has been evaluated throughout tensile–tensile fatigue loading cycles at various steps of the recycling process: The specimens are obtained from flakes after grinding PET wastes (F-r-OPET), from a subsequent homogenization step (r-OPET-hom) and after reactive extrusion (Rex-r-OPET). Virgin PET is also considered as a comparison. First, tensile tests monitored by digital image correlation have been carried out to obtain the elastic modulus and ultimate tensile stress of each type of PET. The fatigue properties of reactive REx-r-OPET increase, probably associated with the rise of cross-linking and branching rates. The fatigue lifespan increases with the macromolecular weight. The fracture surface analysis of specimens brings new insight regarding the factors governing the fatigue behavior and the damaging mode of recycled PET. TiO2 nanoparticles act as stress concentrators, contributing to void formation at multiple sites and thus promoting the fracture process. Finally, the fatigue life of REx-r-OPET is comparable to those of virgin PET. Upcycling opaque PET by reactive extrusion may be a relevant new route to absorb some of the growing amounts of PET worldwide.
Continuously Reinforced Polymeric Composite for Additive Manufacturing—Development and Efficiency Analysis
Authors: Rimkus Arvydas , Farh Mahmoud M. , Gribniak Viktor
Published: August 2022

Additive manufacturing (AM) is a rapidly growing technology, referring to a 3D design process by which digital data builds a physical object in layers by depositing the printed material. The AM has evolved in the aviation, automotive, and medical industries. The AM development for fiber-reinforced composites is the point of current interest, with most research focused on using short fibers. However, notwithstanding particular technological complexities, continuous filaments have superior tensile properties compared to short fibers. Therefore, this manuscript develops an adaptive continuous reinforcement approach for AM based on polymeric material extrusion (ME) technology. It combines the raw material production process, including the ability to vary constituents (e.g., filament materials, reinforcement percentage, and recycled plastic replacement ratio), and the reinforcement efficiency analysis regarding the experimentally verified numerical model. The literature review has identified compatible materials for ensuring sustainable and high-performance plastic composites reinforced with continuous fibers. In addition, it identified the applicability of recycled polymers in developing ME processes. Thus, the study includes an experimental program to investigate the mechanical performance of 3D printed samples (polylactic acid, PLA, matrix reinforced with continuous aramid filament) through a tensile test. Recycled polymer replaced 40% of the virgin PLA. The test results do not demonstrate the recycled polymer’s negative effect on the mechanical performance of the printed samples. Moreover, the recycled material reduced the PLA cost by almost twice. However, together with the potential efficiency of the developed adaptive manufacturing technology, the mechanical characteristics of the printed material revealed room for printing technology improvement, including the aligned reinforcement distribution in the printed product and printing parameters’ setup.
Structural Properties of Epoxy–Silica Barrier Coatings for Corrosion Protection of Reinforcing Steel
Authors: Uvida Mayara Carla , Almeida Adriana de Araújo , Pulcinelli Sandra Helena , Santilli Celso Valentim , Hammer Peter
Published: August 2022

Reinforcement steel extensively applied in civil construction is susceptible to corrosion due to the carbonation process in reinforced concrete and chloride ions diffusion. Epoxy-silica-based coatings are a promising option to guarantee the long-term stability of reinforced concrete structures. In this study, the influence of the proportion between the poly (bisphenol-A-co-epichlorhydrin) resin (DGEBA) and the curing agent diethylenetriamine (DETA) on the structural, morphological, and barrier properties of epoxy–silica nanocomposites were evaluated. To simulate different stages of concrete aging, electrochemical impedance spectroscopy (EIS) assays were performed for coated samples in a 3.5 wt.% NaCl solution (pH 7) and in simulated concrete pore solutions (SCPS), which represent the hydration environment in fresh concrete (SCPS2, pH 14) and after carbonation (SCPS1, pH 8). The results showed that coatings with an intermediate DETA to DGEBA ratio of 0.4, presented the best long-term corrosion protection with a low-frequency impedance modulus of up to 3.8 GΩ cm2 in NaCl and SCPS1 solutions. Small-angle X-ray scattering and atomic force microscopy analysis revealed that the best performance observed for the intermediate DETA proportion is associated with the presence of larger silica nanodomains, which act as a filler in the cross-linked epoxy matrix, thus favoring the formation of an efficient diffusion barrier.
Inverse Finite Element Approach to Identify the Post-Necking Hardening Behavior of Polyamide 12 under Uniaxial Tension
Authors: Amstutz Cornelia , Weisse Bernhard , Haeberlin Andreas , Burger Jürgen , Zurbuchen Adrian
Published: August 2022

Finite-element (FE) simulations that go beyond the linear elastic limit of materials can aid the development of polymeric products such as stretch blow molded angioplasty balloons. The FE model requires the input of an appropriate elastoplastic material model. Up to the onset of necking, the identification of the hardening curve is well established. Subsequently, additional information such as the cross-section and the triaxial stress state inside the specimen is required. The present study aims to inversely identify the post-necking hardening behavior of the semi-crystalline polymer polyamide 12 (PA12) at different temperatures. Our approach uses structural FE simulations of a dog-bone tensile specimen in LS-DYNA with mesh sizes of 1 mm and 2 mm, respectively. The FE simulations are coupled with an optimization routine defined in LS-OPT to identify material properties matching the experimental behavior. A Von Mises yield criterion coupled with a user-defined hardening curve (HC) were considered. Up to the beginning of necking, the Hockett–Sherby hardening law achieved the best fit to the experimental HC. To fit the entire HC until fracture, an extension of the Hockett–Sherby law with power-law functions achieved an excellent fit. Comparing the simulation and the experiment, the following coefficient of determination R2 could be achieved: Group I: R2 > 0.9743; Group II: R2 > 0.9653; Group III: R2 > 0.9927. Using an inverse approach, we were able to determine the deformation behavior of PA12 under uniaxial tension for different temperatures and mathematically describe the HC.
Improving Thermal Conductivity of Injection Molded Polycarbonate/Boron Nitride Composites by Incorporating Spherical Alumina Particles: The Influence of Alumina Particle Size
Authors: Zhou Chuxiang , Bai Yang , Zou Huawei , Zhou Shengtai
Published: August 2022

In this work, the influences of alumina (Al2O3) particle size and loading concentration on the properties of injection molded polycarbonate (PC)/boron nitride (BN)/Al2O3 composites were systematically studied. Results indicated that both in-plane and through-plane thermal conductivity of the ternary composites were significantly improved with the addition of spherical Al2O3 particles. In addition, the thermal conductivity of polymer composites increased significantly with increasing Al2O3 concentration and particle size, which were related to the following factors: (1) the presence of spherical Al2O3 particles altered the orientation state of flaky BN fillers that were in close proximity to Al2O3 particles (as confirmed by SEM observations and XRD analysis), which was believed crucial to improving the through-plane thermal conductivity of injection molded samples; (2) the presence of Al2O3 particles increased the filler packing density by bridging the uniformly distributed BN fillers within PC substrate, thereby leading to a significant enhancement of thermal conductivity. The in-plane and through-plane thermal conductivity of PC/50 μm-Al2O3 40 wt%/BN 20 wt% composites reached as high as 2.95 and 1.78 W/mK, which were 1183% and 710% higher than those of pure PC, respectively. The prepared polymer composites exhibited reasonable mechanical performance, and excellent electrical insulation properties and processability, which showed potential applications in advanced engineering fields that require both thermal conduction and electrical insulation properties.
Electrospun ZnO/Pd Nanofibers as Extremely Sensitive Material for Hydrogen Detection in Oxygen Free Gas Phase
Authors: Platonov Vadim , Nasriddinov Abulkosim , Rumyantseva Marina
Published: August 2022

The development of safety sensors is an urgent necessity for the successful use of hydrogen in real conditions, which may differ, in particular, by the oxygen content in the surrounding atmosphere. Palladium-modified zinc oxide shows the high sensitivity when detecting hydrogen in air; however, studies of the sensor properties and the operation mechanism of the ZnO/Pd sensor when reducing gases are detected in an oxygen deficient or inert atmosphere have not been effectuated. In this work, we synthesized the ZnO and ZnO/Pd nanofibers by electrospinning and for the first time determined their sensor properties in the detection of CO, NH3 and H2 in different oxygen backgrounds. The microstructure and composition of nanofibers were characterized by electron microscopy, X-ray diffraction, X-ray fluorescent spectroscopy, and X-ray photoelectron spectroscopy. The interaction with the gas phase was investigated in situ by diffuse reflectance IR Fourier transform spectroscopy (DRIFTS). The sensor properties of ZnO and ZnO/Pd nanofibers were studied at 100–450 °C towards CO, NH3 and H2 in the N2/O2 gas mixtures containing 0.0005–20% O2. When detecting CO, a decrease in the oxygen concentration from 20 to 0.0005% in the gas phase does not lead to a significant change in the sensor response. At the same time, when detecting NH3 and especially H2, a decrease in oxygen concentration down to 0.0005% results in the dramatic increase in the sensor response of ZnO/Pd nanofibers. This result is discussed in terms of palladium hydride formation, modulation of the potential barrier at the ZnO/Pd interface, as well as changes in the concentration of donor defects and charge carriers in the ZnO matrix. Synthesized electrospun ZnO/Pd nanofibers are extremely promising materials for sensors for detecting hydrogen in an oxygen free atmosphere.
Filling-Balance-Oriented Parameters for Multi-Cavity Molds in Polyvinyl Chloride Injection Molding
Authors: Tsai Hsi-Hsun , Wu Shao-Jung , Liu Jia-Wei , Chen Sin-He , Lin Jui-Jung
Published: August 2022

PVC injection molding has constrained temperature and shear rate owing to its temperature sensitivity and high viscosity, as well as its low conductivity. Many challenges are associated with the PVC injection molding process used for producing PVC fittings with a multi-cavity mold. Once filling imbalance occurs, the gates and/or runner of the mold should be changed by machine tools, which is time- and cost-intensive. Using Moldex3D and the Taguchi method, this study reveals an approach to eliminate imbalanced filling of multi-cavity molds for PVC injection molding. The injection rate optimization of the filling stage is successfully verified to reduce the imbalance. Furthermore, the temperatures of the molded PVC fittings are only slightly increased by the change in injection rate. The temperatures of fittings in the filling and packing are lower than the degradation temperature of PVC. This approach may help technicians to obtain pilot-run samples for the optimization of molding parameters and ensure degradation-free PVC molding.
Comparative Studies on Carbon Paste Electrode Modified with Electroactive Polyamic Acid and Corresponding Polyimide without/with Attached Sulfonated Group for Electrochemical Sensing of Ascorbic Acid
Authors: Hwang Jiunn-Jer , Bibi Aamna , Chen Yu-Ci , Luo Kun-Hao , Huang Hsiang-Yuan , Yeh Jui-Ming
Published: August 2022

In this study, electroactive poly (amic acid) (EPAA) and corresponding polyimide (EPI) without or with a sulfonated group (i.e., S-EPAA, and S-EPI) were prepared and applied in electrochemical sensing of ascorbic acid (AA). The electroactive polymers (EAPs) containing EPAA/EPI and S-EPAA/S-EPI were synthesized by using an amine-capped aniline trimer (ACAT) and sulfonated amine-capped aniline trimer (S-ACAT) as an electroactive segment that controlled the redox capability and influenced the degree of sensitivity of the EAPs towards AA. Characterization of the as-prepared EAPs was identified by FTIR spectra. The redox capability of the EAPs was investigated by electrochemical cyclic voltammetric studies. It should be noted that the redox capability of the EAPs was found to show the following trend: S-EPAA > S-EPI > EPAA > EPI. For the electrochemical sensing studies, a sensor constructed from an S-EPAA-modified carbon paste electrode (CPE) demonstrated 2-fold, 1.27-fold, and 1.35-fold higher electro-catalytic activity towards the oxidation of AA, compared to those constructed using a bare CPE, S-EPI-, and EPI/EPAA-modified CPE, respectively. The higher redox capability of S-EPAA-modified CPE exhibited a good electrochemical response towards AA at a low oxidative potential, with good stability and selectivity. Moreover, an electrochemical sensor constructed from S-EPAA-modified CPE was found to reveal better selectivity for a tertiary mixture of AA/DA/UA, as compared to that of EPI-modified, EPAA-modified and S-EPI-modified CPE, based on a series of differential pulse voltammograms.
Effect of Coir Fiber Surface Treatment on Interfacial Properties of Reinforced Epoxy Resin Composites
Authors: Ru Shaofeng , Zhao Can , Yang Songmei , Liang Dong
Published: August 2022

Coir-fiber-reinforced epoxy resin composites are an environmentally friendly material, and the use of coir fibers improves the mechanical properties of epoxy resin. In order to improve the interfacial adhesion between coir fibers and the epoxy resin matrix, microwave treatment, alkali treatment, acetic anhydride modification, 3-aminopropyltriethoxysilane modification and their reasonable combination method treatments were carried out on coir fibers, respectively. Scanning electron microscopy (SEM), Fourier transform-infrared (FTIR) and X-ray diffraction (XRD) were used to analyze the effects of the different treatments on the characteristics of the coir fibers, and single-fiber pullout tests were performed on the pullout specimens made from the above coir fibers. The results calculated by the proposed estimation method show that the combination method of alkali treatment and 3-aminopropyltriethoxysilane surface modification could better enhance the interfacial bonding ability between coir fibers and epoxy resin with an interfacial shear strength and pullout energy of 6.728 MPa and 40.237 N·mm, respectively. The principal analysis shows that the method can form both mechanical interlocking and chemical bonds at the interface to enhance the interfacial bonding ability. This study provides a more suitable method for improving the interfacial properties of coir-fiber-reinforced epoxy resin composites and has implications for the study of natural fiber composites.
Estimation of the Effects of CO2 and Temperature on the Swelling of PS-CO2 Mixtures at Supercritical Conditions on Rheological Testing
Authors: Ibarra-Garza César Miguel , Treviño-Quintanilla Cecilia D. , Bonilla-Ríos Jaime
Published: August 2022

The use of supercritical CO2 as a blowing agent for polymeric foams instead of traditional blowing agents has been a trend in recent years. To achieve the final desired properties of the polymeric foams, the rheological behavior of the material needs to be reliable. The polymer swelling in the samples for rheological testing affects the results of the viscoelastic properties of the material. This study proposes a new testing methodology to control the accuracy and repeatability of the rheological characterization for PS-SCO2 samples. To develop this methodology, three polystyrene resins with different molecular weight distribution were studied at three temperatures (170, 185 and 200 °C) and three pressures (0.1 MPa, 6.89 MPa and 13.78 MPa). The CO2 concentration was estimated and used in the Sanchez–Lacombe Equation of State (SLEOS) to determine the polymer swelling, as it affects the dimensions of specimens tested in high-pressure rheometers. The correction factors provided a consistent trend in the viscosity with respect to temperature and a decrease of up to 50% in the standard deviation. The results of this study are crucial for an accurate measurement of viscoelastic properties by parallel-plate rheometry.
Silicon Carbide Nanoparticles as a Mechanical Boosting Agent in Material Extrusion 3D-Printed Polycarbonate
Authors: Petousis Markos , Vidakis Nectarios , Mountakis Nikolaos , Grammatikos Sotirios , Papadakis Vassilis , David Constantine N. , Moutsopoulou Amalia , Das Subrata C.
Published: August 2022

In this work, the effect of silicon carbide (carborundum, SiC), as a boosting agent of the mechanical response of the polycarbonate (PC) polymer, was investigated. The work aimed to fabricate nanocomposites with an improved mechanical performance and to further expand the utilization of 3D printing in fields requiring an enhanced material response. The nanocomposites were produced by a thermomechanical process in various SiC concentrations in order to evaluate the filler loading in the mechanical enhancement. The samples were 3D printed with the material extrusion (MEX) method. Their mechanical performance was characterized, following international standards, by using dynamic mechanical analysis (DMA) and tensile, flexural, and Charpy’s impact tests. The microhardness of the samples was also measured. The morphological characteristics were examined, and Raman spectra revealed their structure. It was found that SiC can improve the mechanical performance of the PC thermoplastic. A 19.5% increase in the tensile strength was found for the 2 wt.% loading nanocomposite, while the 3 wt.% nanocomposite showed a 16% increase in the flexural strength and a 35.9% higher impact strength when compared to the unfilled PC. No processability issues were faced for the filler loadings that have been studied here.
Performance, Combustion, and Emission Comparisons of a High-Speed Diesel Engine Fueled with Biodiesel with Different Ethanol Addition Ratios Based on a Combined Kinetic Mechanism
Authors: Zhong Yunhao , Zhang Yanhui , Mao Chengfang , Ukaew Ananchai
Published: August 2022

In this work, different ethanol ratios (5%, 10%, 15%, and 20%) blended with biodiesel were used to investigate the effects of ethanol addition on engine performance, combustion, and emission characteristics of a high-speed diesel engine in terms of brake power, brake specific fuel consumption, brake thermal efficiency, cylinder pressure, cylinder temperature, heat release rate, NOx, CO, and soot emissions. First, a three-dimensional CFD model was established by AVL-Fire combined with the CHEMKIN code. Then, an improved kinetic mechanism with 430 reactions and 122 species was developed by combining a three-component biodiesel combustion mechanism and ethanol mechanism to accurately simulate the blended fuel combustion processes. The results indicated that compared with biodiesel, the maximum brake specific fuel consumption increased by 6.08%, and the maximum brake thermal efficiency increased by 2.09% for the blended fuel. In addition, NOx and CO emissions for EE20 were reduced by 29.32% and 39.57% at full engine load. Overall, the ethanol addition can significantly decrease pollution emissions.
Performance of a Novel Enhanced Sparrow Search Algorithm for Engineering Design Process: Coverage Optimization in Wireless Sensor Network
Authors: Liu Rui , Mo Yuanbin
Published: August 2022

Burgeoning swarm intelligence techniques have been creating a feasible theoretical computational method for the modeling, simulation, and optimization of complex systems. This study aims to increase the coverage of a wireless sensor network (WSN) and puts forward an enhanced version of the sparrow search algorithm (SSA) as a processing tool to achieve this optimization. The enhancement of the algorithm covers three aspects. Firstly, the Latin hypercube sampling technique is utilized to generate the initial population to obtain a more uniform distribution in the search space. Secondly, a sine cosine algorithm with adaptive adjustment and the Lévy flight strategy are introduced as new optimization equations to enhance the convergence efficiency of the algorithm. Finally, to optimize the individuals with poor fitness in the population, a novel mutation disturbance mechanism is introduced at the end of each iteration. Through numerical tests of 13 benchmark functions, the experimental results show that the proposed enhanced algorithm can converge to the optimum faster and has a more stable average value, reflecting its advantages in convergence speed, robustness, and anti-local extremum ability. For the WSN coverage problem, this paper established a current optimization framework based on the swarm intelligence algorithms, and further investigated the performance of nine algorithms applied to the process. The simulation results indicate that the proposed method achieves the highest coverage rate of 97.66% (on average) among the nine algorithms in the calculation cases, which is increased by 13.00% compared with the original sparrow search algorithm and outperforms other methods by 1.47% to 15.34%.
Using Social Media to Assess Expressions of Gratitude to God: Issues for Consideration
Authors: Tay Louis , Thapa Stuti , Newman David B. , Choudhury Munmun De
Published: August 2022

With the proliferation of technology-based communication, public expressions of gratitude to God on social media have become more pervasive. At the same time, data science approaches are increasingly being applied to social media language data to assess positive human attributes. We elucidate critical considerations in assessing public expressions of gratitude to God, including language variability and comparability, degree of authenticity, machine learning language analysis, and aggregation approaches that could affect assessment accuracy.
Visual Threats and Visual Efficacy: Ideas of Image Reception in the Arguments of Lucas Tudense about the Changes in the Crucifixion (c.1230)
Authors: Carreño Sara
Published: August 2022

In this paper, I examine the ideas regarding image reception that can be extracted from the De altera uita, a theological treatise written by the Iberian bishop Lucas de Tui in ca. 1230. In this book, he devotes one chapter to rejecting the changes that were taking place at the time in the image of the Crucifixion, especially concerning the variation in the number of nails and the shape of the cross. I will show that this text provides illuminating references regarding image reception, mainly through Lucas’s concerns about the visual misleading of the faithful and their devotional responses to artworks. By examining this work, which I will set against the theological and devotional background of its time, I will argue that this treatise reflects the importance of sight within the religious experience of late-medieval Europe.
50 Years of Criticizing Religion: A Historical Overview of Norwegian Religious Education
Authors: Jarmer Sebastian Tjelle
Published: August 2022

The critique of religion is hotly debated in contemporary media, legal and educational discourses. This review takes almost 50 years (1976–2022) of Norwegian research on the critique of religion in religious education as a point of departure to highlight how the discourse on the critique of religion is negotiated and represented. The review showcases the intimate connection between historical contexts and discursive repertoires through historical and critical discourse analysis. The analysis showcases that the discourse on the critique of religion is dynamic and diverse—starting mainly to appear through theological discourses referencing internal and hermeneutical critique before developing into more diverse discourses emanating from multiple actors and genres centered around critical thinking, source-evaluation, intercultural competence, and negative criticism of religion.
Ten Years of VIIRS EDR Imagery Validation and User Interactions
Authors: Hillger Donald , Line William E. , Seaman Curtis , Miller Steven D. , Finley Steve , Kopp Thomas J.
Published: August 2022

Over ten years of Visible Infrared Imaging Radiometer Suite (VIIRS) Environmental Data Records (EDR) Imagery Team activities have included primarily imagery validation, but also product generation and display and user interactions. VIIRS imagery validation starts with pre-launch preparations leading up to producing first-light imagery shortly after the launch of each Joint Polar Satellite System (JPSS) satellite. Imagery quality is scrutinized for typical imagery visualization problems, as well as the overall ability to utilize VIIRS imagery for analysis and forecasting purposes. Then, long-term monitoring of imagery continues through the lifetime of each VIIRS instrument. The VIIRS EDR Imagery Team has undertaken four major ground system code changes. The first of these code changes was needed in 2013 when Near Constant Contrast (NCC) Imagery at night was not routinely being generated from the Day-Night Band (DNB) due to incorrect sensitivity limits. The second applied Terrain Correction to the VIIRS EDR Imagery in 2020. The third, in 2021, was needed to fix an imagery banding anomaly in the NCC, which was masked for years by the natural variability of most NCC Imagery. The fourth was the increase from 6 M-band EDRs to all 16 M-band EDRs in 2021, allowing for the display of true-color and other multi-band imagery products from VIIRS Imagery EDRs. Here, we summarize the efforts of the VIIRS EDR Imagery Team which have resulted in a valuable suite of quality-controlled imagery products for the user community.
Multisensor Data Fusion by Means of Voxelization: Application to a Construction Element of Historic Heritage
Authors: Raimundo Javier , Lopez-Cuervo Medina Serafin , Aguirre de Mata Julian , Prieto Juan F.
Published: August 2022

Point clouds are very common tools used in the work of documenting historic heritage buildings. These clouds usually comprise millions of unrelated points and are not presented in an efficient data structure, making them complicated to use. Furthermore, point clouds do not contain topological or semantic information on the elements they represent. Added to these difficulties is the fact that a variety of different kinds of sensors and measurement methods are used in study and documentation work: photogrammetry, LIDAR, etc. Each point cloud must be fused and integrated so that decisions can be taken based on the total information supplied by all the sensors used. A system must be devised to represent the discrete set of points in order to organise, structure and fuse the point clouds. In this work we propose the concept of multispectral voxels to fuse the point clouds, thus integrating multisensor information in an efficient data structure, and applied it to the real case of a building element in an archaeological context. The use of multispectral voxels for the fusion of point clouds integrates all the multisensor information in their structure. This allows the use of very powerful algorithms such as automatic learning and machine learning to interpret the elements studied.
Spatial Trend and Impact of Snowmelt Rate in Spring across China’s Three Main Stable Snow Cover Regions over the Past 40 Years Based on Remote Sensing
Authors: Wu Xuejiao , Zhu Rao , Long Yinping , Zhang Wei
Published: August 2022

Historical patterns of snow cover and snowmelt are shifting due to climate warming and perhaps some human activities, threatening natural water resources and the ecological environment. Passive microwave remote sensing provides quantitative data for snow mass evaluation. Here, we evaluated the long-term impact of climate warming on snowmelt rates, using snow water equivalent (SWE) datasets derived from passive microwave remotely sensed data over China’s three main stable snow cover regions during the past 40 years (1981–2020). The results showed that higher ablation rates in spring were found in locations with a deeper SWE because of high snowmelt rates that occurred in late spring and early summer in areas with a deeper snowpack. Annual maximum SWE (snow water equivalent) has declined across two out of the three main mountains of China’s snow cover regions over the past 40 years under climate warming. The maximum and mean snowmelt rate was ca. 30 and 3 mm/day, respectively, over the three regions. Further, due to SWE being reduced in these deep snowpack areas, moderate and high rates of snowmelt showed trends of decline after 2000. Accordingly, an earlier snow onset day (average 0.6~0.7 day/a) and slower snowmelt rates characterized the mountainous areas across the three main snow cover regions. The slower snowmelt rate is also closely related to vegetation improvement over the three main stable snow cover regions. Therefore, not only vegetation in spring but also streamflow and other ecological processes could be affected by the pronounced changes in SWE and snowmelt rates. These findings strengthen our understanding of how to better assess ecological and environmental changes towards the sustainable use of freshwater resources in spring and earlier summer months in snow-rich alpine regions.
MID: A Novel Mountainous Remote Sensing Imagery Registration Dataset Assessed by a Coarse-to-Fine Unsupervised Cascading Network
Authors: Feng Ruitao , Li Xinghua , Bai Jianjun , Ye Yuanxin
Published: August 2022

The geometric registration of mountainous remote sensing images is always a challenging project, as terrain fluctuations increase the complexity. Deep learning, with its superior computing power and data-driven nature, promises to solve this problem. However, the lack of an appropriate dataset limits the development of deep learning technology for mountainous remote sensing image registration, which it still an unsolved problem in photogrammetry and remote sensing. To remedy this problem, this paper presents a manually constructed imagery dataset of mountainous regions, called the MID (mountainous imagery dataset). To create the MID, we use 38 images from the Gaofen-2 satellite developed by China and generated 4093 pairs of reference and sensed image patches, making this the first real mountainous dataset to our knowledge. Simultaneously, we propose a fully unsupervised, convolutional-network-based iterative registration scheme for the MID. First, the large and global deformation of the reference and sensed images is reduced using an affine registration module, generating the coarse alignment. Then, the local and varied distortions are learned and eliminated progressively using a hybrid dilated convolution (HDC)-based encoder–decoder module with multistep iterations, achieving fine registration results. The HDC aims to increase the receptive field without blocking the artifacts, allowing for the continuous characteristics of the mountainous images of a local region to be represented. We provide a performance analysis of some typical registration algorithms and the developed approach for the MID. The proposed scheme gives the highest registration precision, achieving the subpixel alignment of mountainous remote sensing images. Additionally, the experimental results demonstrate the usability of the MID, which can lay a foundation for the development of deep learning technology in large mountainous remote sensing image registration tasks.
Correlation Analysis of CO2 Concentration Based on DMSP-OLS and NPP-VIIRS Integrated Data
Authors: Zuo Chen , Gong Wei , Gao Zhiyu , Kong Deyi , Wei Ruyi , Ma Xin
Published: August 2022

In view of global warming, caused by the increase in the concentration of greenhouse gases, China has proposed a series of carbon emission reduction policies. It is necessary to obtain the spatiotemporal distribution of carbon emissions accurately. Nighttime light data is recognized as an important basis for carbon emission estimation. A large number of research results show that there is a positive correlation between nighttime light intensity and carbon emission. However, in the current context of China’s industrial reforms, this positive relationship may not be entirely correct. First, we correct the nighttime light data from different satellites and established a long-term series data set. Then, we verify the positive correlation between nighttime light and carbon emission. However, the time scale of emission data often lags, and the carbon concentration data are released earlier and are more accurate than emission data. Therefore, we propose to investigate the relationship between nighttime light and carbon concentration. It is found that there may be different correlations between nighttime light and the carbon concentration, due to different urban industrial structure and development planning. Therefore, by exploring the relationship between nighttime light and the carbon concentration, the existing carbon emission estimation model can be modified to improve the accuracy of the emission model.
Optimization of Samples for Remote Sensing Estimation of Forest Aboveground Biomass at the Regional Scale
Authors: Shu Qingtai , Xi Lei , Wang Keren , Xie Fuming , Pang Yong , Song Hanyue
Published: August 2022

Accurately estimating forest aboveground biomass (AGB) based on remote sensing (RS) images at the regional level is challenging due to the uncertainty of the modeling sample size. In this study, a new optimizing method for the samples was suggested by integrating variance function in Geostatistics and value coefficient (VC) in Value Engineering. In order to evaluate the influence of the sample size for RS models, the random forest regression (RFR), nearest neighbor (K-NN) method, and partial least squares regression (PLSR) were conducted by combining Landsat8/OLI imagery in 2016 and 91 Pinus densata sample plots in Shangri-La City of China. The mean of the root mean square error (RMSE) of 200 random sampling tests was adopted as the accuracy evaluation index of the RS models and VC as a relative cost index of the modeling samples. The research results showed that: (1) the statistical values (mean, standard deviation, and coefficient of variation) for each group of samples based on 200 experiments were not significantly different from the sampling population (91 samples) by t-test (p = 0.01), and the sampling results were reliable for establishing RS models; (2) The reliable analysis on the RFR, K-NN, and PLSR models with sample groups showed that the VC decreases with increasing samples, and the decreasing trend of VC is consistent. The number of optimal samples for RFR, K-NN, and PLSR was 55, 54, and 56 based on the spherical model of variance function, respectively, and the optimal results were consistent. (3) Among the established models based on the optimal samples, the RFR model with the determination coefficient R2 = 0.8485, RMSE = 12.25 Mg/hm2, and the estimation accuracy P = 81.125% was better than K-NN and PLSR. Therefore, they could be used as models for estimating the aboveground biomass of Pinus densata in the study area. For the optimal sample size and sampling population, the RFR model of Pinus densata AGB was established, combining 26 variable factors in the study area. The total AGB with the optimal samples was 1.22 × 107 Mg, and the estimation result with the sampling population was 1.24 × 107 Mg based on Landsat8/OLI images. Respectively, the average AGB was 66.42 Mg/hm2 and 67.51 Mg/hm2, with a relative precision of 98.39%. The estimation results of the two sample groups were consistent.
Asian Rice Calendar Dynamics Detected by Remote Sensing and Their Climate Drivers
Authors: Zhang Jing , Wu Huaqing , Zhang Zhao , Zhang Liangliang , Luo Yuchuan , Han Jichong , Tao Fulu
Published: August 2022

Detecting crop calendar changes is critically important for crop monitoring and management, but the lack of annual, Asia-wide, and long-term rice calendar datasets limits our understanding of rice phenological changes and their climate drivers. In this study, we retrieved key rice phenological dates from the GLASS AVHRR LAI through combining threshold-based and inflection-based detection methods, analyzed the changes during the period 1995–2015, and identified the key climate drivers of the main rice seasons in Asia. The retrieved phenological dates had a high level of agreement with the referenced observations. All R2 were greater than 0.80. The length of the vegetation growing period (VGP) was mostly shortened (by an average of −4 days per decade), while the length of the reproductive growing period was mostly prolonged (by an average of 2 days per decade). Moreover, solar radiation had the most significant impact on the rice calendar changes, followed by the maximum and minimum temperatures. The VGP in tropical areas is the most sensitive to climate change. Our study extends the annual rice phenology dynamics to a higher spatial–temporal resolution and provides new insights into rice calendar changes and their climate drivers, which will assist governments and researchers regarding food security and agricultural sustainability.
Fast Segmentation and Dynamic Monitoring of Time-Lapse 3D GPR Data Based on U-Net
Authors: Shang Ke , Zhang Feizhou , Song Ao , Ling Jianyu , Xiao Jiwen , Zhang Zihan , Qian Rongyi
Published: August 2022

As the amount of ground-penetrating radar (GPR) data increases significantly with the high demands of nondestructive detection methods under urban roads, a method suitable for time-lapse data dynamic monitoring should be developed to quickly identify targets on GPR profiles and compare time-lapse datasets. This study conducted a field experiment aiming to monitor one backfill pit using three-dimensional GPR (3D GPR), and the time-lapse data collected over four months were used to train U-Net, a fast neural network based on convolutional neural networks (CNNs). Consequently, a trained network model that could effectively segment the backfill pit from inline profiles was obtained, whose Intersection over Union (IoU) was 0.83 on the test dataset. Moreover, segmentation masks were compared, demonstrating that a change in the southwest side of the backfill pit may exist. The results demonstrate the potential of machine learning algorithms in time-lapse 3D GPR data segmentation and dynamic monitoring.
Stereovision-Based Ego-Motion Estimation for Combine Harvesters
Authors: Chen Haiwen , Chen Jin , Guan Zhuohuai , Li Yaoming , Cheng Kai , Cui Zhihong
Published: August 2022

Ego-motion estimation is a foundational capability for autonomous combine harvesters, supporting high-level functions such as navigation and harvesting. This paper presents a novel approach for estimating the motion of a combine harvester from a sequence of stereo images. The proposed method starts with tracking a set of 3D landmarks which are triangulated from stereo-matched features. Six Degree of Freedom (DoF) ego motion is obtained by minimizing the reprojection error of those landmarks on the current frame. Then, local bundle adjustment is performed to refine structure (i.e., landmark positions) and motion (i.e., keyframe poses) jointly in a sliding window. Both processes are encapsulated into a two-threaded architecture to achieve real-time performance. Our method utilizes a stereo camera, which enables estimation at true scale and easy startup of the system. Quantitative tests were performed on real agricultural scene data, comprising several different working paths, in terms of estimating accuracy and real-time performance. The experimental results demonstrated that our proposed perception system achieved favorable accuracy, outputting the pose at 10 Hz, which is sufficient for online ego-motion estimation for combine harvesters.
Global Trends on Rotavirus Vaccine’s Studies
Authors: UYAR Cemile , MIZRAKÇI Serpil
Published: August 2022

Objective: The aim of the current study was to investigate global research trends and collaborations on the Rotavirus vaccines. Methods: We conducted bibliometric research in this study on the Web of Science database with the keywords related to the rotavirus vaccine. And also visualization techniques were used for mapping the collaborations. We only included the research articles and review articles. Results: We reached 5093 publications according to our search, and 52.916% were published as open access. The most preferred publication languages were English (96.682%). Most of the articles (13.627%) on the rotavirus vaccine were published in the Vaccine journal. The publications were from 164 countries globally. Most of the publications were from the United States of America (USA) (42.981%), England (9.641%), India (6.892%), Australia (6.146%), and Belgium (5.910%). The Centers For Disease Control Prevention, League of European Research Universities Leru, and World Health Organization (WHO) were the leading affiliations on rotavirus vaccine studies. The H indexes of the publications from the USA were higher (H index: 127), but the Belgian publications’ average number of citations per publication was the highest. Conclusions: The quantity of papers on the rotavirus vaccine has increased over time. The Centers for Disease Control and Prevention, the League of European Research Universities Leru, and the WHO were the most active institutions, and the USA was the most productive country. The number of publications from countries where the disease is common was below the desired level.