bluuebunny/crossref_metadata_2025 huggingface dataset:
The Rhodamine–Perylene Compact Electron Donor–Acceptor Dyad: Spin-Orbit Charge-Transfer Intersystem Crossing and the Energy Balance of the Triplet Excited States
Authors: Imran Muhammad , Liu Dongyi , Ye Kaiyue , Zhang Xue , Zhao Jianzhang
Published: January 2024

We prepared a rhodamine (RB)–perylene (Pery) compact electron donor/acceptor dyad (RB–Pery) to study the spin-orbit charge-transfer intersystem crossing (SOCT–ISC). The UV–vis absorption spectrum indicates a negligible electronic interaction between the donor and acceptor at ground state. However, the fluorescence of both the RB and Pery units are quenched in the dyad, which is attributed to the photoinduced electron transfer, supported by the electrochemical studies. Nanosecond transient absorption (ns-TA) spectra show delocalized triplet states, i.e., there is an excited-state equilibrium between Pery and the RB triplet states. The triplet state lifetime was determined as 109.8 μs. With intermolecular triplet–triplet energy transfer, monitored using ns-TA spectra, the triplet-state energy balance between RB and Pery in RB–Pery was confirmed. The proposed cascade photophysical processes of the dyad are 1RB*-Pery→RB–Pery+•→[3RB*-Pery↔RB-3Pery*]. Moreover, long-lived rhodamine radical cation (in milliseconds) was detected in both deaerated/aerated non-polar or low-polarity solvents (i.e., p-xylene, toluene). The potential energy curve of the dyad against the variation in the dihedral angle between the two units indicates large torsional freedom (53°~128°) in RB–Pery, which leads to inefficient SOCT–ISC; consequently, low singlet-oxygen quantum yields (ΦΔ = 2~8%) were observed.
Performance of Orbital Angular Momentum Communication for a Non-Uniformly Correlated High-Order Bessel–Gaussian Beam in a Turbulent Atmosphere
Authors: Cong Zihan , Zhang Hui , Gao Yaru , Cai Yangjian , Yuan Yangsheng
Published: January 2024

We derived the formula for the detection probability, signal-to-noise ratio (SNR), and average bit error rate (BER) for the signal orbital angular momentum (OAM) state carried via non-uniformly correlated high-order Bessel–Gaussian beam propagation in a turbulent atmosphere. The wavelength, receiver aperture, beam width, strength of the turbulent atmosphere, and topological charge effect on detection probability, SNR, and average BER of the signal OAM state were demonstrated numerically. The results show that the signal OAM state with low topological charge, a small receiver aperture, a narrow beam width, and a long wavelength can improve the performance of optical communications systems under conditions of weak atmospheric turbulence. Our results will be useful in long-distance free space optical (FSO) communications.
Oblique-Incidence Interferometric Measurement of Optical Surface Based on a Liquid-Crystal-on-Silicon Spatial Light Modulator
Authors: Zeng Zhen , Jiang Chengzhao , Jia Yuxuan , Zhai Zhongsheng , Zhang Xiaodong
Published: January 2024

An oblique-incidence interferometric measurement method is proposed to measure and adjust optical surfaces with a liquid-crystal-on-silicon spatial light modulator (LCoS-SLM). The optical system only consists of an interferometer and an LCoS-SLM with precision mounts. It could reduce the measuring cost and time consumption due to the programmable function of the LCoS-SLM and offer the ability to align the optical system. The oblique-incidence measurement theory and optical system adjustment method are established based on an off-axis paraboloid model. The ray-tracing program to calculate the compensation phase map in the measurement is proposed with math models. In the optical alignment step, the off-axis paraboloid model is used to apply the LCoS-SLM as a phase compensator to generate a focusing spot or light spot array to adjust the measured optical surface. And in the interferometric measurement step, the calculated compensation phase map from the ray-tracing calculation is loaded on the LCoS-SLM using the same optical setup as the optical alignment step without any mechanical adjustment. Two interference measurement experiments of typical optical surfaces were carried out to verify the accuracy of the measuring system.
Functional Characterization of ShK Domain-Containing Protein in the Plant-Parasitic Nematode Bursaphelenchus xylophilus
Authors: Mendonça Madalena , Vicente Cláudia S. L. , Espada Margarida
Published: January 2024

ShK domain-containing proteins are peptides found in different parasitic and venomous organisms. From a previous transcriptomic dataset from Bursaphelenchus xylophilus, a plant-parasitic nematode that infects forest tree species, we identified 96 transcripts potentially as ShK domain-containing proteins with unknown function in the nematode genome. This study aimed to characterize and explore the functional role of genes encoding ShK domain-containing proteins in B. xylophilus biology. We selected and functionally analyzed nine candidate genes that are putatively specific to B. xylophilus. In situ hybridization revealed expression of one B. xylophilus ShK in the pharyngeal gland cells, suggesting their delivery into host cells. Most of the transcripts are highly expressed during infection and showed a significant upregulation in response to peroxide products compared to the nematode catalase enzymes. We reported, for the first time, the potential involvement of ShK domain genes in oxidative stress, suggesting that these proteins may have an important role in protecting or modulating the reactive oxygen species (ROS) activity of the host plant during parasitism.
Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event
Authors: Antonopoulos Chrissi , Dillon H. E. , Gall Elliott
Published: January 2024

Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of PM2.5 reached 280 μg/m3, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor PM2.5 concentrations in residences during extreme wildfire smoke events.
Gold Nanoclusters Synthesized within Single-Chain Nanoparticles as Catalytic Nanoreactors in Water
Authors: Pinacho-Olaciregui Jokin , Verde-Sesto Ester , Taton Daniel , Pomposo José A.
Published: January 2024

Metalloenzymes are able to catalyze complex biochemical reactions in cellular (aqueous) media with high efficiency. In recent years, a variety of metal-containing single-chain nanoparticles (SCNPs) have been synthesized as simplified metalloenzyme-mimetic nano-objects. However, most of the metal-containing SCNPs reported so far contained complexed metal ions but not metal nanoclusters (NCs) with diameter <5 nm, which could be used as powerful, emerging catalysts. Herein, we report the synthesis of gold nanoclusters (Au-NCs) within SCNPs and the further use of Au-NCs/SCNPs as catalytic nanoreactors in water. We demonstrate that a common motif contained in several drugs (i.e., the aminophenyl–oxazolidinone fragment present in Rivaroxaban, Sutezolid, and Linezolid) can be efficiently prepared in water from a hydrophobic precursor compound by using the Au-NCs/SCNPs as efficient catalytic nanoreactors. In summary, this work paves the way forthe synthesis of metal–NCs/SCNPs for advanced catalysis in aqueous media.
Features of Changes in the Structure and Properties of a Porous Polymer Material with Antibacterial Activity during Biodegradation in an In Vitro Model
Authors: Yudin Vladimir V. , Kulikova Tatyana I. , Morozov Alexander G. , Egorikhina Marfa N. , Rubtsova Yulia P. , Charykova Irina N. , Linkova Daria D. , Zaslavskaya Maya I. , Farafontova Ekaterina A. , Kovylin Roman S. , Aleinik Diana Ya. , Chesnokov Sergey A.
Published: January 2024

Hybrid porous polymers based on poly-EGDMA and polylactide containing vancomycin, the concentration of which in the polymer varied by two orders of magnitude, were synthesized. The processes of polymer biodegradation and vancomycin release were studied in the following model media: phosphate-buffered saline (PBS), trypsin-Versene solution, and trypsin-PBS solution. The maximum antibiotic release was recorded during the first 3 h of extraction. The duration of antibiotic escape from the polymer samples in trypsin-containing media varied from 3 to 22 days, depending on the antibiotic content of the polymer. Keeping samples of the hybrid polymer in trypsin-containing model media resulted in acidification of the solutions—after 45 days, up to a pH of 1.84 in the trypsin-Versene solution and up to pH 1.65 in the trypsin-PBS solution. Here, the time dependences of the vancomycin release from the polymer into the medium and the decrease in pH of the medium correlated. These data are also consistent with the results of a study of the dynamics of sample weight loss during extraction in the examined model media. However, while the polymer porosity increased from ~53 to ~60% the pore size changed insignificantly, over only 10 μm. The polymer samples were characterized by their antibacterial activity against Staphylococcus aureus, and this activity persisted for up to 21 days during biodegradation of the material, regardless of the medium type used in model. Surface-dependent human cells (dermal fibroblasts) adhere well, spread out, and maintain high viability on samples of the functionalized hybrid polymer, thus demonstrating its biocompatibility in vitro.
The Effect of Coupling Agents and Graphene on the Mechanical Properties of Film-Based Post-Consumer Recycled Plastic
Authors: Choi Sungwoong , Zhao Jianxiang , Lee Patrick C. , Choi Duyoung
Published: January 2024

This study aims to improve the mechanical properties of post-consumer recycled (PCR) plastic composed primarily of polypropylene (PP) and polyethylene (PE), which generally exhibit poor miscibility, by applying coupling agents and graphene. Here, we compare a commercially available coupling agent with a directly synthesized maleic anhydride (MA) coupling agent. When applied to a 5:5 blend of recycled PP and PE, an optimum tensile strength was achieved at a 3 wt% coupling agent concentration, with the MA coupling agent outperforming the commercial one. Characterization through Fourier transform infrared spectroscopy (FT-IR) and thermogravimetry analysis (TGA) revealed a PP:PE ratio of approximately 3:7 in the PCR plastics, with 4.86% heterogeneous materials present. Applying 3 wt% of the commercial and MA coupling agents to the PCR plastics resulted in a significant 53.9% increase in the tensile strength, reaching 11.25 MPa, and a remarkable 421.54% increase in the melt flow index (MFI), reaching 25.66 g/10 min. Furthermore, incorporating 5 wt% graphene led to a notable 64.84% increase in the tensile strength. In addition, the application of MA coupling agents and graphene improved the thermal stability of the PCR plastics. These findings show significant promise for addressing environmental concerns associated with plastic waste by facilitating the recycling of PCR plastics into new products. The utilization of coupling agents and graphene offers a viable approach to enhance the mechanical properties of PCR plastics, paving the way for sustainable and environmentally friendly solutions.
Glass Transition Temperatures and Thermal Conductivities of Polybutadiene Crosslinked with Randomly Distributed Sulfur Chains Using Molecular Dynamic Simulation
Authors: Alamfard Tannaz , Lorenz Tommy , Breitkopf Cornelia
Published: January 2024

The thermal conductivities and glass transition temperatures of polybutadiene crosslinked with randomly distributed sulfur chains having different lengths from mono-sulfur (S1) to octa-sulfur (S8) were investigated. The thermal conductivities of the related models as a function of the heat flux autocorrelation function, applying an equilibrium molecular dynamic (EMD) simulation and the Green–Kubo method, were studied for a wide range of temperatures. The influence of the length of sulfur chains, degree of crosslinking, and molar mass of the crosslinker on the glass transition temperature and final values of thermal conductivities were studied. First, the degree of crosslinking is considered constant for the eight simulation models, from mono-sulfur (S1) to octa-sulfur (S8), while the molar mass of the sulfur is increases. The results show that the thermal conductivities of the crosslinked structure decrease with increasing temperature for each model. Moreover, by increasing the lengths of the sulfur chains and the molar weight of the crosslinker, thermal conductivity increases at a constant temperature. The MD simulation demonstrates that the glass transition temperature and density of the crosslinked structure enhance as the length of the sulfur chains and molar mass of the sulfur increase. Second, the molar weight of sulfur is considered constant in these eight models; therefore, the degree of crosslinking decreases with the increase in the lengths of the sulfur chains. The results show that the thermal conductivities of the crosslinked structure decrease with the increase in the temperature for each model. Moreover, by increasing the lengths of sulfur chains and thus decreasing the degree of crosslinking, the trend in changes in thermal conductivities are almost the same for all of these models, so thermal conductivity is constant for a specific temperature. In addition, the glass transition temperature and density of the crosslinked structure decrease.
Study of Heterogeneity of Ethylene/1-Octene Copolymers Synthesized with Zirconium and Titanium Complexes Bearing Diamine-bis(phenolate) Ligands
Authors: Białek Marzena , Wiechoczek Dominika
Published: January 2024

A series of ethylene/1-octene copolymers synthesized with diamine-bis(phenolate) complexes activated with Al(iBu)3/[Ph3C][B(C6F5)4] were subjected to preparative temperature rising elution fractionation (TREF). The complexes used differed in the type of metallic center (Zr or Ti) or the amine donor in the pendant arm of the ligand (NMe2 or NiPr2). The obtained fractions were then characterized via FTIR, DSC and GPC methods. It was found that all the copolymers had very broad chemical composition distributions, and the most heterogeneous was the copolymer produced by the titanium complex bearing a ligand with the NiPr2 donor group. The difference in the comonomer incorporation into the macromolecules of the fractions was as high as 8.3 mol%. The melting temperature and molecular weight of the fractions changed nearly linearly with the increased elution temperature. Copolymers produced by zirconium catalysts were also fractionated by molecular weight using the solvent/non-solvent technique with subsequent analysis of the fractions. It was shown that the fractions have a similar composition, low molecular weight distribution and very broad comonomer distribution. Therefore, the comonomer content in the fractions was not a function of the molecular weight as was observed for the copolymers synthesized with the Ziegler–Natta catalysts.
Investigating Sedimentation Behavior of Montmorillonite Flocs between Flat Plates in a 2D System Using Image Analysis
Authors: Roknujjaman Md , Yoshida Keisuke , Bin Ghazali Muhamad Ezral , Li Jiawei , Kyotoh Harumichi , Adachi Yasuhisa , Asada Yohei
Published: January 2024

The sedimentation of flocs in aquatic environments is a fundamental phenomenon that has not yet been fully elucidated. This study quantitatively examines sedimentation behavior, particularly focusing on sedimentation turbulence, in a two-dimensional system between flat plates, utilizing image analysis. Experiments were conducted in a rectangular container with montmorillonite suspensions coagulated in a sodium chloride solution. The settling motion of flocs was visualized using a green laser from above and captured horizontally with a digital camera. The study employed Particle Image Velocimetry (PIV) to analyze the velocity field in floc sedimentation, using the flocs as tracers to calculate the mean velocity at the sediment–supernatant interface. The results showed that the mean PIV value is affected by rising particles caused by sedimentation turbulence, indicating that PIV analysis of flow fields using flocs as tracers is reliable. The maximum settling velocity was found to increase with the initial interface height and the thickness of the container. The study further notes that flow velocity fluctuations increase during rapid sedimentation, marked by repeated collisions, separation, and the flocculation of variably sized flocs, offering a clear explanation of sedimentation turbulence. Additionally, Fourier analysis of vertical spectra in the container reflects the formation and collapse of flocs.
Applications of Electric Heating Technology in Vehicle Exhaust Pollution Control
Authors: Li Kai , Xiao Bing , Wang Yanjun , Jia Jianli , Wu Xiaodong
Published: January 2024

Motor vehicle exhaust is an important cause of atmospheric pollution. Nowadays, mainstream exhaust emission aftertreatment technologies, such as TWC, DOC, SCR, and DPF, usually require sufficient temperature to perform good purification or maintain normal working conditions. Compared with exhaust gas heating technologies such as engine enrichment and fuel injection, electric heating technology can quickly increase the temperature of exhaust gas aftertreatment devices without adverse effects on engine operating conditions. This article introduces the research and progress of electric heating technology combined with traditional aftertreatment devices on major types of vehicles, such as gasoline vehicles, diesel vehicles, motorcycles, and hybrid vehicles, to improve exhaust purification efficiency and its accompanying fuel consumption impact. In addition, the common structure and characteristics of electric heaters, as well as the current status and development trend of electric heating unit technologies such as electric heating power supply are introduced.
The Effects of Psilocybin on Lipopolysaccharide-Induced Inflammation in THP-1 Human Macrophages
Authors: Ghasemi Gojani Esmaeel , Wang Bo , Li Dongping , Kovalchuk Olga , Kovalchuk Igor
Published: January 2024

Psilocybin, an innate compound produced by mushrooms belonging to the Psilocybe genus, is primarily known for its agonistic effects on the serotonin 5-HT2A receptor. This receptor’s functioning is involved in many neurological processes. In the context of this research, our primary aim was to comprehensively investigate the influence of psilocybin as a serotonin receptor agonist on the intricate cascade of events involved in THP-1 macrophages stimulated by lipopolysaccharide (LPS). THP-1 monocyte cells were subjected to differentiation into macrophages through a controlled incubation with phorbol 12-myristate 13-acetate (PMA). The next step involved the induction of an inflammatory response by exposing THP-1 macrophages to 500 ng/mL LPS for 4 h. Subsequently, we triggered the activation of the second phase of the NLRP3 inflammasome by introducing adenosine triphosphate (ATP) immediately following LPS stimulation. Our findings have revealed a dose-dependent inverse correlation between psilocybin exposure and the production of LPS-induced proinflammatory cytokines and proteins. Our work indicates that psilocybin likely mediates these responses by influencing key signaling pathways, including NF-κB, IL-6/TYK2/STAT3, and TYK2/STAT1.
Decolonial Pastoral Care for Cultural Trauma: Pastoral Theological Intervention in the Korean Context
Authors: Kwak Hamin
Published: January 2024

This essay examines the connectedness between cultural trauma theory and decolonial studies in pastoral theology, demonstrating the denotation of collective trauma in South Korea and Korean Christianity from past colonial and war experiences. Although cultural trauma theory is well established in studying the case of the Holocaust and Western context, it has not yet explored the trauma of the Third World in a fully fledged manner. Rather, it still employs a Western-centered discourse that is unable to explain the disparity of power dynamics based on colonial values. Therefore, a critical analysis is essential to develop a decolonial discourse between cultural trauma theory and pastoral theology. The case of Korean cultural trauma and its relation to Korean Protestantism is a good starting point for addressing decolonial pastoral care in that the Korean church is still complicit in the colonial religious inheritances concerning its colonized ways of thinking and psyche. Throughout this essay, I argue that Korean social identity and Protestantism are reproducing the harmful reaction of in-group exclusion under the impact of cultural trauma. Finally, I provide a pastoral theological analysis of this discussion in order to suggest a new possibility of decolonial pastoral care for the traumatized Korean society and Christianity.
King Lear and the Ethics of Brutal, Caring Faith
Authors: Pfannkoch Tommy
Published: January 2024

This essay engages with King Lear to perform an ethical meditation. The essay finds within the play an ethic resembling the ethics of care: health and flourishing are present not merely in individual human beings but in bonds between human beings. King Lear sets this ethic within a context characterized by finality and human finitude and frailty. Human beings must act within a ripe moment, without being able to consider every contingency and possibility; these acts can (and probably do) affect the wellbeing of those around the actor; and once these acts are completed, they are irrevocable. King Lear sets this state of affairs against a backdrop of indifferent, intractable realms of nature, the divine, and politics. Nevertheless, the essay finds in King Lear the possibility that human beings will grant one another the gift of dignity—even within all that is bleak, contingent, and absurd—a possibility that is ultimately grounded in faith.
Rheumato(Philes): A Publication Option for Rheumatology Devotees’ Creative Works
Authors: Rothschild Bruce M.
Published: January 2024

This journal for Rheumato(philes) has provided a vehicle for the interdisciplinary sharing of the challenges and interventions of our specialty. The provision of state-of-the-art information is not at the expense of the basics from which it has grown. From its initial status as a source of discomfort, a review of back pain diagnostics and therapeutics provides a background for facilitating contemporary practice. We have met the enemy in the form of COVID-19, addressing its many rheumatologic complications, and have been introduced to the vagaries of IgG4 disease. Our clinical skills are tested in recognition of primary hypertrophic osteoarthropathy. The relationship of dental health to rheumatoid arthritis and nutritional issues is currently undergoing scientific review. A unique feature, one we seldom seem to discuss, is the evaluation of disease manifestations when the customary tools are not available. The latter brings us full circle in the evolution of our field. When our colleagues found diagnostic or treatment approaches elusive, they did not call for Ghostbusters; they called for us.
Evaluation of Geographical and Annual Changes in Rice Planting Patterns Using Satellite Images in the Flood-Prone Area of the Pampanga River Basin, the Philippines
Authors: Hosonuma Kohei , Aida Kentaro , Ballaran Vicente , Nagumo Naoko , Sanchez Patricia Ann J. , Sumita Tsuyoshi , Homma Koki
Published: January 2024

Floods are some of the most devastating crop disasters in Southeast Asia. The Pampanga River Basin in the Philippines is a representative flood-prone area, where cultivation patterns vary according to the flood risk. However, quantitative analyses of the effects of flooding on cultivation patterns remain quite limited. Accordingly, this study analyzed MODIS LAI data (MCD15A2H) from 2007 to 2022 to evaluate annual and geographical differences in cultivation patterns in the Candaba municipality of the basin. The analysis consisted of two stages of hierarchical clustering: a first stage for area classification and a second stage for the classification of annual LAI dynamics. As a result, Candaba was divided into four areas, which were found to be partly consistent with the observed flood risk. Subsequently, annual LAI dynamics for each area were divided into two or three clusters. Obvious differences among clusters were caused by flooding in the late rainy season, which delayed the start of planting in the dry season. Clusters also indicated that cultivation patterns slightly changed over the 16 years of the study period. The results of this study suggest that the two-stage clustering approach provided an effective tool for the analysis of MODIS LAI data when considering cultivation patterns characterized by annual and geographical differences.
Edge Effects in Amazon Forests: Integrating Remote Sensing and Modelling to Assess Changes in Biomass and Productivity
Authors: Bauer Luise , Huth Andreas , Bogdanowski André , Müller Michael , Fischer Rico
Published: January 2024

The tropical forests in the Amazon store large amounts of carbon and are still considered a carbon sink. There is evidence that deforestation can turn a forest landscape into a carbon source due to land use and forest degradation. Deforestation causes fragmented forest landscapes. It is known from field experiments that forest dynamics at the edge of forest fragments are altered by changes in the microclimate and increased tree mortality (“edge effects”). However, it is unclear how this will affect large fragmented forest landscapes, and thus the entire Amazon region. The aim of this study is to investigate different forest attributes in edge and core forest areas at high resolution, and thus to identify the large-scale impacts of small-scale edge effects. Therefore, a well-established framework combining forest modelling and lidar-generated forest structure information was combined with radar-based forest cover data. Furthermore, forests were also analyzed at the landscape level to investigate changes between highly fragmented and less-fragmented landscapes. This study found that the aboveground biomass in forest edge areas is 27% lower than in forest core areas. In contrast, the net primary productivity is 13% higher in forest edge areas than in forest core areas. In the second step, whole fragmented landscapes were analyzed. Nearly 30% of all forest landscapes are highly fragmented, particularly in the regions of the Arc of Deforestation, on the edge of the Andes and on the Amazon river banks. Less-fragmented landscapes are mainly located in the central Amazon rainforest. The aboveground biomass is 28% lower in highly fragmented forest landscapes than in less-fragmented landscapes. The net primary productivity is 13% higher in highly fragmented forest landscapes than in less-fragmented forest landscapes. In summary, fragmentation of the Amazon rainforest has an impact on forest attributes such as biomass and productivity, with mostly negative effects on forest dynamics. If deforestation continues and the proportion of highly fragmented forest landscapes increase, the effect may be even more intense. By combining lidar, radar and forest modelling, this study shows that it is possible to map forest structure, and thus the degree of forest degradation, over a large area and derive more detailed information about the carbon dynamics of the Amazon region.
Baseline Climatology of the Canary Current Upwelling System and Evolution of Sea Surface Temperature
Authors: Mills Lara , Janeiro João , Martins Flávio
Published: January 2024

Global climate change has induced a rise in sea surface temperature (SST), although this increase is not uniform across the world. Significant variations exist between coastal and offshore waters, particularly in regions affected by upwelling processes. This study focuses on the Canary Current Upwelling System (CCUS), stretching from Northwest Iberia to Northwest Africa. High-resolution remotely sensed SST data (0.05°) from the ODYSSEA Level 4 Sea Surface Temperature Reprocessed dataset were validated with in situ measurements and employed to establish a regional climatological baseline for 1982–2012. Subsequent years were compared to this baseline to construct SST anomaly maps, revealing SST changes since 2012. The study area was further divided into sub-regions for comparative analysis. Results indicate that SST consistently increased at a higher rate offshore compared to the adjacent nearshore regions. A reference dataset spanning 1951–1981 was used to gauge SST variability between the two baselines. SST exhibited a 0.59 °C increase from 1951–1981 to 1982–2012, with a slowing of SST trends beyond the 1982–2012 baseline. This research offers valuable insights into the climatological dynamics of the CCUS. These findings enhance our understanding of this critical coastal system’s climatology, laying the groundwork for future investigations into evolving climate patterns in coastal regions.
Towards Automated Target Picking in Scalar Magnetic Unexploded Ordnance Surveys: An Unsupervised Machine Learning Approach for Defining Inversion Priors
Authors: McGinnity Claire , Kolster Mick Emil , Døssing Arne
Published: January 2024

With advancements in both the quality and collection speed of magnetic data captured by uncrewed aerial vehicle (UAV)-based systems, there is a growing need for robust and efficient systems to automatically interpret such data. Many existing conventional methods require manual inspection of the survey data to pick out candidate areas for further analysis. We automate this initial process by implementing unsupervised machine learning techniques to identify small, well-defined regions. When further analysis is conducted with magnetic inversion algorithms, then our approach also reduces the nonlinear computation and time costs by breaking one huge inversion problem into several smaller ones. We also demonstrate robustness to noise and sidestep the requirement for large quantities of labeled training data: two pitfalls of current automation approaches. We propose first to use hierarchical clustering on filtered magnetic gradient data and then to fit ellipses to the resulting clusters to identify subregions for further analysis. In synthetic data experiments and on real-world datasets, our model successfully captures all true targets while simultaneously proposing fewer computationally costly false positives. With this approach, we take an important step towards fully automating the detection of high-risk subregions, but we wish to emphasize the importance of prudent skepticism until it has been tested and proven on more diverse data.
A Comparison of Different Machine Learning Methods to Reconstruct Daily Evapotranspiration Time Series Estimated by Thermal–Infrared Remote Sensing
Authors: Zhao Gengle , Song Lisheng , Zhao Long , Tao Sinuo
Published: January 2024

Remote sensing-based models usually have difficulty in generating spatio-temporally continuous terrestrial evapotranspiration (ET) due to cloud cover and model failures. To overcome this problem, machine learning methods have been widely used to reconstruct ET. Therefore, studies comparing and evaluating the accuracy and effectiveness of reconstruction among different machine learning methods at the basin scale are necessary. In this study, four popular machine learning methods, including deep forest (DF), deep neural network (DNN), random forest (RF) and extreme gradient boosting (XGB), were used to reconstruct the ET product, addressing gaps resulting from cloud cover and model failure. The ET reconstructed by the four methods was evaluated and compared for Heihe River Basin. The results showed that the four methods performed well for Heihe River Basin, but the RF method was particularly robust. It not only performed well compared with ground measurements (R = 0.73) but also demonstrated the ability to fully reconstruct gaps generated by the TSEB model across the entire basin. Validation based on ground measurements showed that the DNN and XGB models performed well (R > 0.70). However, some gaps still existed in the desert after reconstruction using the DNN and XGB models, especially for the XGB model. The DF model filled these gaps throughout the basin, but this model had lower consistency compared with ground measurements (R = 0.66) and yielded many low values. The results of this study suggest that machine learning methods have considerable potential in the reconstruction of ET at the basin scale.
Radar Reconnaissance Pulse-Splitting Modeling and Detection Method
Authors: Guo Ronghua , Dong Yang-Yang , Zhang Lidong , Dong Chunxi , Bao Dan , Li Wenbo , Li Zhiyuan
Published: January 2024

When radar receivers adopt digital channelization, it is prone to generating a cross-channel split signal, the rabbit ear effect, and a transition band repeated signal, leading to errors in radar signal sorting or identification. The pulse-splitting model and detection method proposed in this paper can model split pulses and identify them in radar pulse streams, facilitating the merging of split pulses to enhance sorting and identification performance. Firstly, the mechanism of splitting pulse generation is deeply analyzed, and the splitting site theory is proposed. Then, the split pulse signal model and the split pulse number statistical model based on geometric distribution are constructed, which are used to guide the construction of simulation data of split pulse flow with different characteristics. Furthermore, a time-domain convergence degree (TCD) index is proposed to characterize the pulse split phenomenon. At the same time, in order to avoid a large number of threshold searching problems in pulse-splitting detection, an empirical formula for the pulse-splitting detection threshold based on the TCD is given to quickly determine whether there is a pulse train split problem. The selected measured radar pulse stream is verified to follow a geometric distribution at a significance level of 0.05. The proposed method achieved a detection accuracy of at least 99.55% on the simulation dataset and at least 95.68% on the experimental dataset, validating the rationality of pulse-splitting modeling and the effectiveness of the detection method.
Radargrammetric 3D Imaging through Composite Registration Method Using Multi-Aspect Synthetic Aperture Radar Imagery
Authors: Luo Yangao , Deng Yunkai , Xiang Wei , Zhang Heng , Yang Congrui , Wang Longxiang
Published: January 2024

Interferometric synthetic aperture radar (InSAR) and tomographic SAR measurement techniques are commonly used for the three-dimensional (3D) reconstruction of complex areas, while the effectiveness of these methods relies on the interferometric coherence among SAR images with minimal angular disparities. Radargrammetry exploits stereo image matching to determine the spatial coordinates of corresponding points in two SAR images and acquire their 3D properties. The performance of the image matching process directly impacts the quality of the resulting digital surface model (DSM). However, the presence of speckle noise, along with dissimilar geometric and radiometric distortions, poses considerable challenges in achieving accurate stereo SAR image matching. To address these aforementioned challenges, this paper proposes a radargrammetric method based on the composite registration of multi-aspect SAR images. The proposed method combines coarse registration using scale invariant feature transform (SIFT) with precise registration using normalized cross-correlation (NCC) to achieve accurate registration between multi-aspect SAR images with large disparities. Furthermore, the multi-aspect 3D point clouds are merged using the proposed radargrammetric 3D imaging method, resulting in the 3D imaging of target scenes based on multi-aspect SAR images. For validation purposes, this paper presents a comprehensive 3D reconstruction of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) using Ka-band airborne SAR images. It does not necessitate prior knowledge of the target and is applicable to the detailed 3D imaging of large-scale areas with complex structures. In comparison to other SAR 3D imaging techniques, it reduces the requirements for orbit control and radar system parameters. To sum up, the proposed 3D imaging method with composite registration guarantees imaging efficiency, while enhancing the imaging accuracy of crucial areas with limited data.
Integrating Hydrography Observations and Geodetic Data for Enhanced Dynamic Topography Estimation
Authors: Pirooznia Mahmoud , Voosoghi Behzad , Poreh Davod , Amini Arash
Published: January 2024

Dynamic topography (DT) refers to the time-varying component of the sea surface height influenced by factors like ocean currents, temperature, and salinity gradients. Accurate estimation of DT is crucial for comprehending oceanic circulation patterns and their impact on climate. This study introduces two approaches to estimating DT: (1) utilizing satellite altimetry to directly observe sea surface height and (2) considering the steric and non-steric components of sea level anomalies. The steric term is calculated using salinity and temperature data obtained from local buoy data, Argo observations, and the World Ocean Atlas model. The non-steric term is calculated using GRACE Satellite gravimetry data. To estimate the assimilated DT, four methods are utilized, including variance component estimation (VCE), Bayesian theory, Kalman filter, and 3D variational (3DVAR). These methods assimilate the two aforementioned schemes. The validity of the estimated DT is assessed by comparing the calculated sea surface current, derived from the obtained DT, with observations from local current meter stations. The results indicate that the VCE method outperforms other methods in determining the final DT. Furthermore, incorporating the steric and non-steric terms of sea level in determining DT in coastal areas enhances the accuracy of estimating sea surface currents.
Time Lag and Cumulative Effects of Extreme Climate on Coastal Vegetation in China
Authors: Dong Tong , Liu Jing , He Panxing , Shi Mingjie , Chi Yuan , Liu Chao , Hou Yuting , Wei Feili , Liu Dahai
Published: January 2024

Rapid global changes are altering regional hydrothermal conditions, especially in ecologically vulnerable areas such as coastal regions, subsequently influencing the dynamics of vegetation growth. However, there is limited research investigating the response of vegetation in these regions to extreme climates and the associated time lag-accumulation relationships. This study utilized a combined approach of gradual and abrupt analysis to examine the spatiotemporal patterns of vegetation dynamics in the coastal provinces of China from 2000 to 2019. Additionally, we evaluated the time lag-accumulation response of vegetation to extreme climate events. The results showed that (1) extreme high temperatures and extreme precipitation had increased over the past two decades, with greater warming observed in high latitudes and concentrated precipitation increases in water-rich southern regions; (2) both gradual and abrupt analyses indicate significant vegetation improvement in coastal provinces; (3) significant lag-accumulation relationships were observed between vegetation and extreme climate in the coastal regions of China, and the time-accumulation effects were stronger than the time lag effects. The accumulation time of extreme temperatures was typically less than one month, and the accumulation time of extreme precipitation was 2–3 months. These findings are important for predicting the growth trend of coastal vegetation, understanding environmental changes, and anticipating ecosystem evolution.
Analysis of Pre-Seismic Ionospheric Disturbances Prior to 2020 Croatian Earthquakes
Authors: Boudjada Mohammed Y. , Biagi Pier F. , Eichelberger Hans U. , Nico Giovanni , Galopeau Patrick H. M. , Ermini Anita , Solovieva Maria , Hayakawa Masashi , Lammer Helmut , Voller Wolfgang , Pitterle Martin
Published: January 2024

We study the sub-ionospheric VLF transmitter signals recorded by the Austrian Graz station in the year 2020. Those radio signals are known to propagate in the Earth-ionosphere waveguide between the ground and lower ionosphere. The Austrian Graz facility (geographic coordinates: 15.46°E, 47.03°N) can receive such sub-ionospheric transmitter signals, particularly those propagating above earthquake (EQ) regions in the southern part of Europe. We consider in this work the transmitter amplitude variations recorded a few weeks before the occurrence of two EQs in Croatia at a distance less than 200 km from Graz VLF facility. The selected EQs happened on 22 March 2020 and 29 December 2020, with magnitudes of Mw5.4 and Mw6.4, respectively, epicenters localized close to Zagreb (16.02°E, 45.87°N; 16.21°E, 45.42°N), and with focuses of depth smaller than 10 km. In our study we emphasize the anomaly fluctuations before/after the sunrise times, sunset times, and the cross-correlation of transmitter signals. We attempt to evaluate and to estimate the latitudinal and the longitudinal expansions of the ionospheric disturbances related to the seismic preparation areas.
A High-Precision Target Geolocation Algorithm for a Spaceborne Bistatic Interferometric Synthetic Aperture Radar System Based on an Improved Range–Doppler Model
Authors: Xing Chao , Li Zhenfang , Tang Fanyi , Tian Feng , Suo Zhiyong
Published: January 2024

A trend in the development of spaceborne Synthetic Aperture Radar (SAR) technology is the shift from a single-satellite repeated observation mode to a multi-satellite collaborative observation mode. However, current multi-satellite collaborative geolocation algorithms face challenges, such as geometric model mismatch and poor baseline estimation accuracy, arising from highly dynamic changes among multi-satellites. This paper introduces a high-precision and efficient geolocation algorithm for a spaceborne bistatic interferometric SAR (BiInSAR) system based on an improved range–Doppler (IRD) model. The proposed algorithm encompasses three key contributions. Firstly, a comprehensive description of the spatial baseline geometric model unique to the bistatic configuration is provided, with a specific focus on deriving the perpendicular baseline expression. Secondly, IRD geolocation functions are established to meet the specific requirements of the bistatic configuration. Then, a novel BiInSAR geolocation algorithm based on the IRD’s functions is proposed, which can significantly improve the target geolocation accuracy by modifying the range–Doppler equation to suit the bistatic configuration. Meanwhile, a low-coupling parallel calculation method is proposed, which can improve the calculation speed by two to three times. Finally, the accuracy and efficiency of the algorithm are demonstrated using experimental data acquired by the TH-2 satellite, which is China’s first spaceborne BiInSAR system. The experimental results prove that the IRD algorithm exhibits geolocation accuracy with an average error of less than 1 m and a standard deviation of less than 2.5 m while maintaining computational efficiency at a calculation speed of 1,429,678 pixels per second.
Enhancing Animal Production through Smart Agriculture: Possibilities, Hurdles, Resolutions, and Advantages
Authors: Dayoub Moammar , Shnaigat Saida , Tarawneh Radi , Al-Yacoub Azzam , Al-Barakeh Faisal , Al-Najjar Khaled
Published: January 2024

Smart livestock farming utilizes technology to enhance production and meet food demand sustainably. This study employs surveys and case studies to gather data and information, subsequently analyzing it to identify opportunities and challenges. The proposed solutions encompass remote sensing, technology integration, farmer education, and stakeholder engagement. The research delves into smart technologies in animal production, addressing opportunities, challenges, and potential solutions. Smart agriculture employs modern technology to improve efficiency, sustainability, and animal welfare in livestock farming. This includes remote monitoring, GPS-based animal care, robotic milking, smart health collars, predictive disease control, and other innovations. Despite the great promise of smart animal production, there are existing challenges such as cost, data management, and connectivity. To overcome these challenges, potential solutions involve remote sensing, technology integration, and farmer education. Smart agriculture provides opportunities for increased efficiency, improved animal welfare, and enhanced environmental conservation. A well-planned approach is crucial to maximize the benefits of smart livestock production while ensuring its long-term sustainability. This study confirms the growing adoption of smart agriculture in livestock production, with the potential to support the sustainable development goals and deliver benefits such as increased productivity and resource efficiency. To fully realize these benefits and ensure the sustainability of livestock farming, addressing cost and education challenges is essential. Therefore, this study recommends promoting a positive outlook among livestock stakeholders and embracing smart agriculture to enhance farm performance.