bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemical Profile, Antioxidant and Antibacterial Activities, Mechanisms of Action of the Leaf Extract of Aloe arborescens Mill
Authors: Maliehe Tsolanku Sidney , Nqotheni Mduduzi Innocent , Shandu Jabulani Siyabonga , Selepe Tlou Nelson , Masoko Peter , Pooe Ofentse Jacob
Published: February 2023

Aloe arborescens Mill’s extracts have been explored for antibacterial and antioxidant efficacies. However, there is limited information on its chemical composition and mechanism of action. The purpose of this study was to assess the chemical composition, antibacterial and antioxidant activities and mechanism of the whole leaf extract of A. arborescens Mill. The phytochemical profile was analysed with gas chromatography mass spectrometry (GC-MS). The antioxidant and antibacterial activities were screened using 1,1diphenyl2picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and micro-dilution assays, respectively. The effects of the extract on the bacterial respiratory chain dehydrogenase, membrane integrity and permeability were analysed using iodonitrotetrazolium chloride, 260 absorbing materials and relative electrical conductivity assays. GC-MS spectrum revealed 26 compounds with N,N’-trimethyleneurea (10.56%), xanthine (8.57%) and 4-hexyl-1-(7-ethoxycarbonylheptyl)bicyclo[4.4.0]deca-2,5,7-triene (7.10%), being the major components. The extract also exhibited antioxidant activity with median concentration (IC50) values of 0.65 mg/mL on DPPH and 0.052 mg/mL on ABTS. The extract exhibited minimum inhibitory concentration (MIC) values ranging from 0.07 to 1.13 mg/mL. The extract inhibited the bacterial growth by destructing the activity of the respiratory chain dehydrogenase, membrane integrity and permeability. Therefore, the leaf extract has the potential to serve as a source of antibacterial and antioxidant compounds.
Effects of Different Sulfur Compounds on the Distribution Characteristics of Subcellular Lead Content in Arabis alpina L. var. parviflora Franch under Lead Stress
Authors: Xu Cui , Qin Li , Li Yuan , Zu Yanqun , Wang Jixiu
Published: February 2023

Sulfur plays a vital role in the phytoremediation of lead-contaminated soil. The effects of different sulfur forms (S Na2S, and Na2SO4) on lead (Pb) absorption in hyperaccumulator Arabis alpina L. var. parviflora Franch were studied in a soil pot experiment. The subcellular sulfur and lead enrichment characteristics in A. alpina were studied by adding sulfur in different forms and concentrations (0, 75, and 150 mg·kg−1) to Pb-contaminated soil. The results show that the root and shoot biomass increased by 1.94 times under Na2S and Na2SO4 treatment, and the root–shoot ratio of A. alpina increased 1.62 times under the three forms of sulfur treatments, compared with the control. Sulfur content in cell walls and soluble fractions of the root and shoot of A. alpina significantly increased 3.35~5.75 times and decreased 5.85 and 9.28 times in the organelles under 150 mg·kg−1 Na2SO4 treatment. Meanwhile, Pb content in the root and shoot cell walls of A. alpina significantly increased by 3.54 and 2.75 times, respectively. Pb content in the shoot soluble fraction increased by 3.46 times, while it significantly reduced by 3.78 times in the shoot organelle. Pb content in the root organelle and soluble fraction decreased by 2.72 and 2.46 times. Different forms and concentrations of sulfur had no regularity in the effect of Pb and sulfur content in the subcellular components of A. alpina, but the bioconcentration and translocation factors of A. alpina increased compared with the control. Under different concentrations of Na2SO4, there was a significant positive correlation between the contents of sulfur and Pb in the subcellular components of the root of A. alpina (p < 0.05). These results indicate that sulfur application can enhance the Pb resistance of A. alpina by strengthening the cell wall fixation and vacuolar compartmentalization.
A Novel and Highly Inclusive Quantitative Real-Time RT-PCR Method for the Broad and Efficient Detection of Grapevine Leafroll-Associated Virus 1
Authors: Morán Félix , Olmos Antonio , Glasa Miroslav , Silva Marilia Bueno Da , Maliogka Varvara , Wetzel Thierry , Ruiz-García Ana Belén
Published: February 2023

Grapevine (Vitis vinifera L.) is one of the most important crops in the world due to its economic and social impact. Like many other crops, grapevine is susceptible to different types of diseases caused by pathogenic microorganisms. Grapevine leafroll-associated virus 1 (GLRaV-1) is a virus associated with grapevine leafroll disease and it is considered at the national and European level as a pathogen that must be absent in propagative plant material. For this reason, the availability of specific, sensitive and reliable detection techniques to ascertain the sanitary status of the plants is of great importance. The objective of this research was the development of a new GLRaV-1 detection method based on a TaqMan quantitative real-time RT-PCR targeted to the coat protein genomic region and including a host internal control in a duplex reaction. To this end, three new GLRaV-1 full genomes were recovered by HTS and aligned with all sequences available in the databases. The method has been validated following EPPO standards and applied for the diagnosis of field plant material and transmission vectors. The new protocol designed has turned out to be highly sensitive as well as much more specific than the current available methods for the detection and absolute quantitation of GLRaV-1 viral titer.
Temperature Dependence of Metals Accumulation and Removal Kinetics by Arabidopsis halleri ssp. gemmifera
Authors: Kudo Hiroshi , Qian Zhaojie , Inoue Chihiro , Chien Mei-Fang
Published: February 2023

Cadmium (Cd), which is present in zinc (Zn) ore, is a toxic metal and causes contamination globally. Phytoremediation is a promising technology for the remediation of sites with low and moderate contamination. Temperature is an important factor in phytoremediation because it has an impact on both plant biomass and the accumulation of heavy metals. However, little is known about the influence of temperature on heavy metal accumulation by the Cd and Zn hyperaccumulator Arabidopsis halleri ssp. gemmifera. The effect of temperature on the distribution of Cd and Zn in A. halleri ssp. gemmifera and the mechanism of metal removal from solution were investigated in this study. Our results showed that the temperature dependence of the distribution of Cd and Zn in the plant was different, which may suggest that the mechanisms of xylem loading were different between Cd and Zn. Although Cd and Zn have partially similar transport pathways, the removal kinetics based on the first-order reaction rate constant revealed that the temperature which maximized rate of absorption was different between Cd and Zn. This study suggests a potential for efficient Cd phytoextraction using A. halleri ssp gemmifera in Cd and Zn co-existing environments.
Enhancement of the CRISPR/Cas9-Based Genome Editing System in Lettuce (Lactuca sativa L.) Using the Endogenous U6 Promoter
Authors: Riu Young-Sun , Kim Gwang Hoon , Chung Ki Wha , Kong Sam-Geun
Published: February 2023

The CRISPR/Cas9 system has been widely applied as a precise gene-editing tool for studying gene functions as well as improving agricultural traits in various crop plants. Here, we optimized a gene-editing system in lettuce (Lactuca sativa L.) using the endogenous U6 promoter and proved that the PHOT2 gene is a versatile target gene. We isolated the LsU6-10 promoter from 10 U6 snRNA genes identified from the lettuce genome database for comparison with the AtU6-26 promoter that has been used to drive sgRNAs in lettuce. Two CRISPR/Cas9 vectors were constructed using the LsU6-10 and AtU6-26 promoters to drive sgRNA361 to target the PHOT2 gene. The chloroplast avoidance response was defective in lettuces with biallelic mutations in the targeted PHOT2 gene, as in the Arabidopsis phot2 mutant. The PHOT2 gene mutations were stably heritable from the R0 to R2 generations, and the high gene-editing efficiency enabled the selection of transgene-free lines in the R1 generation and the establishment of independent phot2 mutants in the R2 generation. Our results suggest that the LsU6-10 promoter is more effective than the AtU6-26 promoter in driving sgRNA for the CRISPR/Cas9 system in lettuce and that PHOT2 is a useful target gene to verify gene editing efficiency without any detrimental effects on plant growth, which is often a consideration in conventional target genes.
Advances in the Mining of Disease Resistance Genes from Aegilops tauschii and the Utilization in Wheat
Authors: Kou Hongyun , Zhang Zhenbo , Yang Yu , Wei Changfeng , Xu Lili , Zhang Guangqiang
Published: February 2023

Aegilops tauschii is one of the malignant weeds that affect wheat production and is also the wild species ancestor of the D genome of hexaploid wheat (Triticum aestivum, AABBDD). It contains many disease resistance genes that have been lost in the long-term evolution of wheat and is an important genetic resource for the mining and utilization of wheat disease resistance genes. In recent years, the genome sequence of Aegilops tauschii has been preliminarily completed, which has laid a good foundation for the further exploration of wheat disease resistance genes in Aegilops tauschii. There are many studies on disease resistance genes in Aegilops tauschii; in order to provide better help for the disease resistance breeding of wheat, this paper analyzes and reviews the relationship between Aegilops tauschii and wheat, the research progress of Aegilops tauschii, the discovery of disease resistance genes from Aegilops tauschii, and the application of disease resistance genes from Aegilops tauschii to modern wheat breeding, providing a reference for the further exploration and utilization of Aegilops tauschii in wheat disease resistance breeding.
Construction Sheets Made of High-Performance Flame-Retardant Nonwoven Fabrics and Combustion-Resistant Polyurethane Foam: Preparation Process and Property Evaluations
Authors: Shiu Bing-Chiuan , Huang Chen-Hung , Yang Hua-Lin , Chen Yueh-Sheng , Lou Ching-Wen , Lin Jia-Horng
Published: February 2023

In this study, nonwoven fabrics, rigid polyurethane foam (RPUF), Basalt woven fabrics, and an aluminum foil film mold are used to produce multi-functional composite sheets with flame-retardant, sound-absorbing, and electromagnetic-shielding functions. The nonwoven layer is composed of Nomex fibers, flame-retardant PET fibers, and low-melting-point (LMPET) fibers via the needle rolling process. The optimal Nomex fiber/flame-retardant PET fiber/LMPET fiber (N/F/L) nonwoven fabrics are then combined with rigid polyurethane (PU) foam, Basalt woven fabric, and an aluminum foil film mold, thereby producing nonwoven/rigid polyurethane foam/Basalt woven fabric composite sheets that are wrapped in the aluminized foil film. The test results indicate that formed with a foaming density of 60 kg/m3 and 10 wt% of a flame retardant, the composite sheets exhibit electromagnetic interference shielding efficacy (EMI SE) that exceeds 40 dB and limiting oxygen index (LOI) that is greater than 26. The efficient and highly reproducible experimental design proposed in this study can produce multifunctional composite sheets that feature excellent combustion resistance, sound absorption, and EMI SE and are suitable for use in the transportation, industrial factories, and building wall fields.
Coprecipitation of Class II NSAIDs with Polymers for Oral Delivery
Authors: De Marco Iolanda
Published: February 2023

Non-steroidal anti-inflammatory drugs (NSAIDs) are frequently administered orally with modified-release formulations. The attainment of modified-release drugs is commonly achieved through the coprecipitation of the active principle with a biodegradable polymeric carrier in the form of micro or nanoparticles. In this review, some coprecipitation studies of three highly prescribed NSAIDs (in particular, ibuprofen, ketoprofen, and diclofenac sodium) have been analyzed. The techniques employed to micronize the powder, the polymers used, and the main results have been classified according to the type of release required in different categories, such as delayed, immediate, prolonged, sustained, and targeted release formulations. Indeed, depending on the pathology to be treated, it is possible to achieve specific therapeutic objectives, ensuring that the drug is released at a higher or lower dissolution rate (if compared to conventional drugs) and/or at a different time and/or in a specific site of action.
Retentive Forces and Deformation of Fitting Surface in RPD Clasp Made of Polyether-Ether-Ketone (PEEK)
Authors: Vaddamanu Sunil Kumar , Alhamoudi Fahad Hussain , Chaturvedi Saurabh , Alqahtani Nasser M. , Addas Mohamed Khaled , Alfarsi Mohammad Al , Vyas Rajesh , Kanji Masroor Ahmed , Zarbah Mohammad A. , Alqahtani Waleed M. S. , Alqahtani Saeed M. , Abdelmonem Adel M. , Elmahdi Asim Elsir
Published: February 2023

Background: Polyetheretherketone (PEEK) has provided the option to fabricate RPDs with aesthetics unlike metal RPDs, but little attention has been paid to its suitability, especially towards the retentive forces and deformation of the clasp. This study aimed to examine the retentive forces and the fitting surface (inner surface) deformation of clasps made from PEEK and compare it with cobalt–chromium (Co-Cr) clasp. Methods: Forty-two circumferential clasps (14 Co-Cr and 28 PEEK) were fabricated and divided into two groups with clasp undercuts (0.25 mm and 0.5 mm) with thicknesses of 1 mm and 1.5 mm. Each was examined for retentive forces after cycle test on its abutment for 360 cycles. Initial and final retentive forces were recorded. The fitting surface deformation was determined using 3-Matic research analysis software. Results: The results revealed that highest mean initial retentive force was of Co-Cr clasps with 0.50 mm undercut 22.26 N (±10.15 N), and the lowest was the 1 mm PEEK clasps with 0.25 mm undercut 3.35 N (±0.72 N) and highest mean final retentive force was the Co-Cr clasps with 0.50 mm undercut 21.40 N (±9.66 N), and the lowest was the 1 mm PEEK clasps with 0.25 mm undercut 2.71 N (±0.47 N). PEEK clasps had a lower retentive force than Co-Cr clasps with 0.50 undercut. PEEK clasps (1.5 mm) at 0.25 mm undercut had the least deformation (35.3 µm). PEEK showed significantly less deformation (p ≤ 0.014) than Co-Cr. Conclusion: The deformation of PEEK clasps fitting surface was lower than Co-Cr clasps and retentive forces were close to the Co-Cr clasps, suggesting the use of PEEK as an aesthetic clasp option for RPD framework.
New Facet in Viscometry of Charged Associating Polymer Systems in Dilute Solutions
Authors: Gosteva Anna , Gubarev Alexander S. , Dommes Olga , Okatova Olga , Pavlov Georges M.
Published: February 2023

The peculiarities of viscosity data treatment for two series of polymer systems exhibiting associative properties: brush-like amphiphilic copolymers—charged alkylated N-methyl-N-vinylacetamide and N-methyl-N-vinylamine copolymer (MVAA-co-MVACnH2n+1) and charged chains of sodium polystyrene-4-sulfonate (PSSNa) in large-scale molecular masses (MM) and in extreme-scale of the ionic strength of solutions were considered in this study. The interest in amphiphilic macromolecular systems is explained by the fact that they are considered as micellar-forming structures in aqueous solutions, and these structures are able to carry hydrophobic biologically active compounds. In the case of appearing the hydrophobic interactions, attention was paid to discussing convenient ways to extract the correct value of intrinsic viscosity η from the combined analysis of Kraemer and Huggins plots, which were considered as twin plots. Systems and situations were demonstrated where intrachain hydrophobic interactions occurred. The obtained data were discussed in terms of lnηr vs. cη plots as well as in terms of normalized scaling relationships where ηr was the relative viscosity of the polymer solution. The first plot allowed for the detection and calibration of hydrophobic interactions in polymer chains, while the second plot allowed for the monitoring of the change in the size of charged chains depending on the ionic strength of solutions.
Damage Assessment of Roadway Wall Caused by Dynamic and Static Load Action of Gas Explosion
Authors: Jia Zhenzhen , Ye Qing , Li He
Published: February 2023

In order to obtain the damage characteristics of a roadway wall caused by a gas explosion, the damage evaluation theory of a roadway wall under the dynamic and static loads of a gas explosion is analyzed in this paper. Meanwhile, an evaluation method (overpressure–impulse criterion) is selected to evaluate the damage of the roadway wall under the impact load of the gas explosion. A mathematical model and a physical analysis model of the roadway wall damage are established by LS-DYNA software. The dynamic response of the roadway wall caused by the dynamic and static loads of the gas explosion is numerically simulated. The overpressure and impulse of gas explosion propagation are measured, while the damage data of the roadway wall under different overpressure and impulse loads are obtained. The P-I curves of the roadway wall under different dynamic and static loads of gas explosion are drawn. The fitting formula of P-I curves of the roadway wall is obtained. The influence of different geostress loads (0–20 MPa) on the P-I curve is analyzed. The shape of the P-I curve is similar under different geostress conditions. The difference is mainly shown in different sizes of P0 and I0. The numerical simulation results show that the P-I curve and the effect of geostress on roadway wall damage could reflect the dynamic response of the roadway wall. The damage degree and damage range of the roadway wall increase with the increase in explosion load energy. Under the action of different geostresses, the overpressure asymptote P0 and the impulse asymptote I0 show linear changes. The above research results could provide a theoretical basis and data support for the evaluation of roadway wall damage caused by gas explosions.
Assessment of the Explosion Accident Risk in Non-Coal Mining by Hasse Diagram Technique
Authors: Dong Xiaobin , Yang Zhen , Guo Li , Gao Yuan
Published: February 2023

The aim of is paper is to address the problem of identifying critical factors in the analysis of non-coal mine explosion accidents as well as to improve the rationality and accuracy of the risk analysis results. Hence, we developed a risk identification method for non-coal mine explosion accidents, combining the Systems-Theoretic Accident Model and Process (STAMP) and the Rank-order Centroid (ROC) method based on the Poset decision-making theory. The proposed method was applied to identify risk in engineering cases. Findings showed that four main dangerous events (out of twelve identified ones) were the primary culprits of related accidents, which were the events “Blasters without licenses and illegal operation” at the basic level, the event of “the confusion about the safety management system of non-coal mine companies” at the control level, and the event of “the failure about the emergency management departments” and “public security departments” at the supervision level. The approximate values of the average rank of the four events are 11.56, 10.4, 4.33, 4.33. The results of risk identification of non-coal mine explosion accidents based on Poset were consistent with the results obtained by the method used in the case study. This study extends the methods for identifying risks of non-coal mine explosion accidents and facilitates the formulation of effective preventive measures.
A Low-Cost Drive and Detection Scheme for Electrowetting Display
Authors: Luo Zhijie , Peng Cuiling , Liu Yujie , Liu Baoqiang , Zhou Guofu , Liu Shuangyin , Chen Ningxia
Published: February 2023

The electrowetting display (EWD) has obtained much attention as its readability in sunlight and flexible displays. Oil motion control is an important factor for the display performance of EWD. In this paper, we propose a low-cost drive and detection scheme for EWD. The dynamic drive and detection scheme for EWD consists of a low-cost camera, computer and graphical detection system, and portable driving control system. The proposed scheme can detect oil leaking, splitting, and non-recovered defects successfully. Moreover, surface defects such as the hydrophobic layer burned and scratch can also be captured and analyzed by the proposed scheme. We hope that this scheme can provide a drive and detection platform for other EWD researchers.
Effect Sizes for Estimating Differential Item Functioning Influence at the Test Level
Authors: Finch W. Holmes , French Brian F.
Published: February 2023

Differential item functioning (DIF) is a critical step in providing evidence to support a scoring inference in building a validity argument for a psychological or educational assessment. Effect sizes can assist in understanding the accumulation of DIF at the test score level. The current simulation study investigated the performance of several proposed effect size measures under a variety of conditions. Conditions under study included varied sample sizes, DIF effect sizes, the proportion of items with DIF, and the type of DIF (additive vs. non-additive). DIF effect sizes under study included sDTF%, uDTF%, τ^w2, d, R¯Δ2, IDIF2*, and S−DIF−V. The results of this study suggest that across study conditions, τ^w2, IDIF2*, and d were consistently the most accurate measures of the DIF effects. The effect sizes were also estimated in an empirical example. Recommendations and implications for practice are discussed.
Homemaking in and with Migrant Churches as Communities of Care
Authors: Reyes-Espiritu Ma. Adeinev M.
Published: February 2023

Research on migration and religion reports the significance of religion to migrants, particularly those who self-identify as religious. In particular, migrant churches have served as a sanctuary, a venue for social networking, and a community supportive of migrants’ wellbeing, to name a few things. However, migrant churches are also criticized for the possibility of becoming instruments of control over migrants. Heeding Boccagni and Hondagneu-Sotelo’s invitation to use the “homemaking optic” to inquire into the experience of integration of migrants, this paper analyzes how migrant churches foster migrants’ becoming at home in the receiving societies using Philippine migrant communities as a case study. Data is gathered through semi-structured interviews with ministers and pastoral workers in migrant churches. The qualities that characterize their homemaking through belonging to and serving in a migrant church are “identifying with each other”, “creating a shared space”, “advocating for migrants’ rights and welfare”, “sharing resources”, and “adjusting to the receiving society”. The homemaking optic shifts attention towards the subjective realities of migrants against the background of various inequalities that present homemaking as a struggle for many. Migrant churches, through their values, beliefs, and practices, foster an atmosphere that welcomes, supports, encourages, and accompanies migrants towards becoming at home in the receiving country. Using practical theologian LaMothe’s three “dialectical pairs of personal knowing” proposed to underpin just care relationships, I present how migrant churches become communities of care when members, as care receivers, are recognized as they are and whose real “needs and desires” are acknowledged. In this study, the essential role of migrant churches in migrants’ homemaking is examined, emphasizing the notion that churches function as communities of care as they acknowledge the identities, subjectivities, and agency of their members.
To Leave the Land So as Not to Leave the Land: The Religious Motivations of Seasonal Migrants, Including Women, in the Twentieth Century
Authors: Quinn E. Moore
Published: February 2023

This chapter seeks to answer the question as to why, even though subsistence conditions militated against continuing to eke out an existence on unproductive holdings, many inhabitants in Ireland’s western counties did just that. Particularly in the west of Ireland, Irish women and men found ways to remain on their lands and in their dwellings despite the enduring proclivity for permanent migration from Ireland during the second half of the nineteenth century and the first half of the twentieth. The answer lies in the Irish penchant to engage in a variety of vernacular religious practices reiterated via expressive cultural forms like proverbs and reinforced via plays and films. In addition, an otherworld feminine perspective permeated their consciousness. For the Irish, their implicit religion—a complex network of symbols and practices—remained intact, so much so that seasonal migration endured, and the Irish preserved their homelands.
Target Positioning for Complex Scenes in Remote Sensing Frame Using Depth Estimation Based on Optical Flow Information
Authors: Xing Linjie , Yu Kailong , Yang Yang
Published: February 2023

UAV-based target positioning methods are in great demand in fields, such as national defense and urban management. In previous studies, the localization accuracy of UAVs in complex scenes was difficult to be guaranteed. Target positioning methods need to improve the accuracy with guaranteed computational speed. The purpose of this study is to improve the accuracy of target localization while using only UAV information. With the introduction of depth estimation methods that perform well, the localization errors caused by complex terrain can be effectively reduced. In this study, a new target position system is developed. The system has these features: real-time target detection and monocular depth estimation based on video streams. The performance of the system is tested through several target localization experiments in complex scenes, and the results proved that the system can accomplish the expected goals with guaranteed localization accuracy and computational speed.
An Enhanced Residual Feature Fusion Network Integrated with a Terrain Weight Module for Digital Elevation Model Super-Resolution
Authors: Chen Guodong , Chen Yumin , Wilson John P. , Zhou Annan , Chen Yuejun , Su Heng
Published: February 2023

The scale of digital elevation models (DEMs) is vital for terrain analysis, surface simulation, and other geographic applications. Compared to traditional super-resolution (SR) methods, deep convolutional neural networks (CNNs) have shown great success in DEM SR. However, in terms of these CNN-based SR methods, the features extracted by the stackable residual modules cannot be fully utilized as the depth of the network increases. Therefore, our study proposes an enhanced residual feature fusion network (ERFFN) for DEM SR. The designed residual fusion module groups four residual modules to make better use of the local residual features. Meanwhile, the residual structure is refined by inserting a lightweight enhanced spatial residual attention module into each basic residual block to further strengthen the efficiency of the network. Considering the continuity of terrain features, terrain weight modules are integrated into the loss module. Based on two large-scale datasets, our ERFFN shows a 10–20% reduction in the mean absolute error and the lowest error in terrain features, such as slope, demonstrating the superiority of an ERFFN-based DEM SR over state-of-the-art methods. Finally, to demonstrate potential value in real-world applications, we deploy the ERFFN to reconstruct a large geographic area covering 44,000 km2 which contains missing parts.
Fault Detection via 2.5D Transformer U-Net with Seismic Data Pre-Processing
Authors: Tang Zhanxin , Wu Bangyu , Wu Weihua , Ma Debo
Published: February 2023

Seismic fault structures are important for the detection and exploitation of hydrocarbon resources. Due to their development and popularity in the geophysical community, deep-learning-based fault detection methods have been proposed and achieved SOTA results. Due to the efficiency and benefits of full spatial information extraction, 3D convolutional neural networks (CNNs) are used widely to directly detect faults on seismic data volumes. However, using 3D data for training requires expensive computational resources and can be limited by hardware facilities. Although 2D CNN methods are less computationally intensive, they lead to the loss of correlation between seismic slices. To mitigate the aforementioned problems, we propose to predict a 2D fault section using multiple neighboring seismic profiles, that is, 2.5D fault detection. In CNNs, convolution layers mainly extract local information and pooling layers may disrupt the edge features in seismic data, which tend to cause fault discontinuities. To this end, we incorporate the Transformer module in U-net for feature extraction to enhance prediction continuity. To reduce the data discrepancies between synthetic and different real seismic datasets, we apply a seismic data standardization workflow to improve the prediction stability on real datasets. Netherlands F3 real data tests show that, when training on synthetic data labels, the proposed 2.5D Transformer U-net-based method predicts more subtle faults and faults with higher spatial continuity than the baseline full 3D U-net model.
Generation of Non-Linear Technique Based 6 Hourly Wind Reanalysis Products Using SCATSAT-1 and Numerical Weather Prediction Model Outputs
Authors: Bhowmick Suchandra Aich , Gupta Maneesha , Chakraborty Abhisek , Agarwal Neeraj , Sharma Rashmi , Ali Meer Mohammed
Published: February 2023

We combined observations of ocean surface winds from Indian SCATterometer SATellite-1 (SCATSAT-1) with a background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium-Range Weather Forecast (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. We are following the concept from the modern particle filter technique, which does not represent the model probability density function (PDF) as Gaussian. We generated the 6-hourly hybrid winds for 2018 and validated them using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform (CCMP) dataset and global buoy data from National Data Buoy Centre (NDBC). The results suggest the potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and bias along the swath. The study shows that the generated hybrid winds are of prime quality compared with the already existing daily products available from Indian Space Research Organization (ISRO).
Urban Area Characterization and Structure Analysis: A Combined Data-Driven Approach by Remote Sensing Information and Spatial–Temporal Wireless Data
Authors: Chen Xiangyu , Zhang Kaisa , Chuai Gang , Gao Weidong , Si Zhiwei , Hou Yijian , Liu Xuewen
Published: February 2023

Analysis of urban area function is crucial for urban development. Urban area function features can help to conduct better urban planning and transportation planning. With development of urbanization, urban area function becomes complex. In order to accurately extract function features, researchers have proposed multisource data mining methods that combine urban remote sensing and other data. Therefore, the research of efficient multisource data analysis tools has become a new hot topic. In this paper, a novel urban data analysis method combining spatiotemporal wireless network data and remote sensing data was proposed. First, a Voronoi-diagram-based method was used to divide the urban remote sensing images into zones. Second, we combined period and trend components of wireless network traffic data to mine urban function structure. Third, for multisource supported urban simulation, we designed a novel spatiotemporal city computing method combining graph attention network (GAT) and gated recurrent unit (GRU) to analyze spatiotemporal urban data. The final results prove that our method performs better than other commonly used methods. In addition, we calculated the commuting index of each zone by wireless network data. Combined with the urban simulation conducted in this paper, the dynamic changes of urban area features can be sensed in advance for a better sustainable urban development.
Quantifying Emissions from Fugitive Area Sources Using a Hybrid Method of Multi-Path Optical Remote Sensing and Tomographic Inverse-Dispersion Techniques
Authors: Li Sheng , Liu Yanna , Du Ke
Published: February 2023

Reducing methane (CH4) emissions from anthropogenic activities is critical to climate change mitigation efforts. However, there is still considerable uncertainty over the amount of fugitive CH4 emissions due to large-scale area sources and heterogeneous emission distributions. To reduce the uncertainty and improve the spatial and temporal resolutions, a new hybrid method was developed combining optical remote sensing (ORS), computed tomography (CT), and inverse-dispersion modeling techniques on the basis of which a multi-path scanning system was developed. It uses a horizontal radial plume mapping path configuration and adapts a Lagrangian stochastic dispersion mode into CT reconstruction. The emission map is finally calculated by using a minimal curvature tomographic reconstruction algorithm, which introduces smooth constraints at each pixel. Two controlled-release experiments of CH4 were conducted with different configurations, showing relative errors of only 2% and 3%. Compared with results from the single-path inverse-dispersion method (5–175%), the new method can not only derive the emission distribution but also obtain a more accurate emission rate. The outcome of this research would bring broad application of the ORS-CT and inverse-dispersion techniques to other gases and sources.
Evaluation of Habitat Suitability for Asian Elephants in Sipsongpanna under Climate Change by Coupling Multi-Source Remote Sensing Products with MaxEnt Model
Authors: He Kai , Fan Chenjing , Zhong Mingchuan , Cao Fuliang , Wang Guibin , Cao Lin
Published: February 2023

The Asian elephant (Elephas maximus Linnaeus) is a globally endangered species, an internationally protected species, and a first-class protected animal in China. However, future climate change and human activities exacerbate the instability of its habitat range, leading to a possible reduction in the range. By using multi-source remote sensing data and products, as well as climate change models, including ASTER GDEM v3, Landsat8 OLI image and ClimateAP, we examined the effects of ecological factors related to climate and natural and anthropogenic influences on the distribution of Asian elephants in Sipsongpanna. Multiyear elephant field tracking data were used with a MaxEnt species distribution model and the climate model. First, the distribution of Asian elephants in potentially suitable areas in Sipsongpanna was simulated under current climatic conditions without considering human activities. The predicted distribution was verified by existing Asian elephant migration trajectories. Subsequently, the distribution of potentially suitable areas for Asian elephants in Sipsongpanna was simulated under two climate change scenarios (RCP4.5, RCP8.5) in three periods (2025, 2055, and 2085). The changes in potentially suitable areas for Asian elephants in Sipsongpanna were analyzed under multiple climate change scenarios for the current (2017) and different future periods by considering the effects of human activities. The results show the following: (1) under anthropogenic interference (AI), the optimal MaxEnt model has a high prediction accuracy with the area under the curve (AUC) of 0.913. The feature combination (FC) includes linear, quadratic, and threshold features, and the regularization multiplier (RM) is 2.1. (2) Jackknife analyses of the non-anthropogenic interference (NAI) and anthropogenic interference (AI) scenarios indicate that topography (altitude (Alt)), temperature (mean warmest month temperature (MWMT)), and precipitation (mean annual precipitation (MAP)) are the top three factors influencing the distribution of Asian elephants. (3) The total area suitable for Asian elephants under current climate conditions and AI accounts for 46.35% of the total area. Areas of high suitability (occurrence probability >0.5) are located in Jinghong City in central Sipsongpanna and Mengla County in southeastern Sipsongpanna. Among them, the minimum habitat range and ecological corridors are mainly located in Mengman Town, Mohan Town, Mengla Town, Mengban Township, Dadugang Township, and Mengwang Township. (4) The change in potentially suitable areas for Asian elephants between current and future conditions is small under AI and large under undisturbed conditions.
RoadFormer: Road Extraction Using a Swin Transformer Combined with a Spatial and Channel Separable Convolution
Authors: Liu Xiangzeng , Wang Ziyao , Wan Jinting , Zhang Juli , Xi Yue , Liu Ruyi , Miao Qiguang
Published: February 2023

The accurate detection and extraction of roads using remote sensing technology are crucial to the development of the transportation industry and intelligent perception tasks. Recently, in view of the advantages of CNNs in feature extraction, its related road extraction methods have been proposed successively. However, due to the limitation of kernel size, they perform less effectively at capturing long-range information and global context, which are crucial for road targets distributed over long distances and highly structured. To deal with this problem, a novel model named RoadFormer with a Swin Transformer as the backbone is developed in this paper. Firstly, to extract long-range information effectively, a Swin Transformer multi-scale encoder is adopted in our model. Secondly, to enhance the feature representation capability of the model, we design an innovative bottleneck module, in which the spatial and channel separable convolution is employed to obtain fine-grained and globe features, and then a dilated block is connected after the spatial convolution module to capture more integrated road structures. Finally, a lightweight decoder consisting of transposed convolution and skip connection generates the final extraction results. Extensive experimental results confirm the advantages of RoadFormer on the Deepglobe and Massachusetts datasets. The comparative results of visualization and quantification demonstrate that our model outperforms comparable methods.
Hyperspectral Anomaly Detection with Differential Attribute Profiles and Genetic Algorithms
Authors: Wang Hanyu , Yang Mingyu , Zhang Tao , Tian Dapeng , Wang Hao , Yao Dong , Meng Lingtong , Shen Honghai
Published: February 2023

Anomaly detection is hampered by band redundancy and the restricted reconstruction ability of spectral–spatial information in hyperspectral remote sensing. A novel hyperspectral anomaly detection method integrating differential attribute profiles and genetic algorithms (DAPGA) is proposed to sufficiently extract the spectral–spatial features and automatically optimize the selection of the optimal features. First, a band selection method with cross-subspace combination is employed to decrease the spectral dimension and choose representative bands with rich information and weak correlation. Then, the differentials of attribute profiles are calculated by four attribute types and various filter parameters for multi-scale and multi-type spectral–spatial feature decomposition. Finally, the ideal discriminative characteristics are reserved and incorporated with genetic algorithms to cluster each differential attribute profile by dissimilarity assessment. Experiments run on a variety of genuine hyperspectral datasets including airport, beach, urban, and park scenes show that the effectiveness of the proposed algorithm has great improvement with existing state-of-the-art algorithms.
Township Development and Transport Hub Level: Analysis by Remote Sensing of Nighttime Light
Authors: Chen Lijun , Zhang Haiping , Wang Zhiqiang
Published: February 2023

The coordinated development of township and city transportation is expected to reach new heights in the global sustainable transport plans of emerging economies. However, few studies have focused on the transport hub features considering marginal administrative division. This study examines the correlation between township development and hub level by using remote sensing of nightlight imagery. Systematically corrected satellite images of Global NPP-VIIRS Nighttime lights were selected as experimental data. Furthermore, the township hub level model and nighttime light indices were established to demonstrate the correlation characteristics of 6671 townships. Results show that the development level of road transport for a considerable number of townships is positively correlated with the hub level. The positively correlated townships show a spatial clustering distribution. In contrast, several negative correlations and random townships are related to the radiation of adjacent city growth poles and township special industrial characteristics. Nighttime light data can compensate for the difficulty in obtaining socioeconomic data below the prefecture level from a multiscale micro perspective and statistical caliber differences. These findings can be proven to be valuable to planners and designers of township development and regional transport.
Robust Hyperspectral Unmixing with Practical Learning-Based Hyperspectral Image Denoising
Authors: Huang Risheng , Li Xiaorun , Fang Yiming , Cao Zeyu , Xia Chaoqun
Published: February 2023

The noise corruption problem commonly exists in hyperspectral images (HSIs) and severely affects the accuracy of hyperspectral unmixing algorithms. The noise formulation existing in HSIs is relatively complex and would change in conjunction with different devices and imaging settings. For real applications, applying denoising approaches without accurate close-to-reality noise modeling before unmixing may not improve, but rather degrade the unmixing performance. This study proposes a robust hyperspectral unmixing method with practical learning-based hyperspectral image denoising. We formulated a close-to-reality noise model for hyperspectral data and provide a calibration approach for the noise parameters. On the basis of the calibrated noise model, synthetic data were generated and used for training a KST-based denoising network. The noisy hyperspectral data were firstly denoised by the trained denoising network and were then used to perform the unmixing process. A variety of unmixing algorithms can be integrated into our method to improve the accuracy of unmixing in noisy situations. In the experiments, several widely used unmixing algorithms were employed to verify the effect of the proposed method. The experimental results on both synthetic and real demonstrated that our proposed method can handle HSI data with various gain settings and helps to improve the unmixing performance effectively.
Classification of Alteration Zones Based on Drill Core Hyperspectral Data Using Semi-Supervised Adversarial Autoencoder: A Case Study in Pulang Porphyry Copper Deposit, China
Authors: Yang Xu , Chen Jianguo , Chen Zhijun
Published: February 2023

With the development of hyperspectral technology, it has become possible to classify alteration zones using hyperspectral data. Since various altered rocks are comprehensive manifestations of mineral assemblages, their spectra are highly similar, which greatly increases the difficulty of distinguishing among them. In this study, a Semi-Supervised Adversarial Autoencoder (SSAAE) was proposed to classify the alteration zones, using the drill core hyperspectral data collected from the Pulang porphyry copper deposit. The multiscale feature extractor was first integrated into the encoder to fully exploit and mine the latent feature representations of hyperspectral data, which were further transformed into discrete class vectors using a classifier. Second, the decoder reconstructed the original inputs with the latent and class vectors. Third, we imposed a categorical distribution on the discrete class vectors represented in the one-hot form using the adversarial regularization process and incorporated the supervised classification process into the network to better guide the network training using the limited labeled data. The comparison experiments on the synthetic dataset and measured hyperspectral dataset were conducted to quantitatively and qualitatively certify the effect of the proposed method. The results show that the SSAAE outperformed six other methods for classifying alteration zones. Moreover, we further displayed the delineated results of the SSAAE on the cross-section, in which the alteration zones were sensible from a geological point of view and had good spatial consistency with the occurrence of Cu, which further demonstrates that the SSAAE had good applicability for the classification of alteration zones.
An Advanced Data Processing Algorithm for Extraction of Polarimetric Radar Signatures of Moving Automotive Vehicles Using the H/A/α Decomposition Technique
Authors: Bosma Detmer A. , Krasnov Oleg A. , Yarovoy Alexander
Published: February 2023

A dedicated signal and data processing chain is proposed for a fully polarimetric Doppler surveillance S-band radar to extract the polarimetric signatures of moving targets. To extract the target’s polarimetric features, detection, clustering, and tracking steps are realized for a multi-target environment in the range-Doppler domain. A dedicated data fusion method for all four polarimetric radar channel signals is implemented to take full advantage of the additional polarimetric information and improve the detection performance. While tracking each particular target, polarization information is collected and used to describe their polarization scattering characteristics. Using the polarimetric H/A/α decomposition technique, the polarimetric features of moving automotive targets are extracted and investigated. The developed processing chain has been applied to the signals scattered from vehicles moving in a highway. By employing both time averaging and spatial averaging of the statistical coherency matrix, the polarimetric signatures of both moving vehicles and static clutter have been presented in the two-dimensional H/α plane. It has been found that the spatial averaging approach results in polarimetric signatures of moving vehicles that give the opportunity to directly and without consideration of the motion of the targets compare the polarization features of moving targets and static clutter. Therefore, this method can be used to improve the performance of target detection or target classification.