bluuebunny/crossref_metadata_2025 huggingface dataset:
Crotamine/siRNA Nanocomplexes for Functional Downregulation of Syndecan-1 in Renal Proximal Tubular Epithelial Cells
Authors: Campeiro Joana D’Arc , Dam Wendy A. , Hayashi Mirian A. F. , van den Born Jacob
Published: May 2023

Proteinuria drives progressive tubulointerstitial fibrosis in native and transplanted kidneys, mainly through the activation of proximal tubular epithelial cells (PTECs). During proteinuria, PTEC syndecan-1 functions as a docking platform for properdin-mediated alternative complement activation. Non-viral gene delivery vectors to target PTEC syndecan-1 could be useful to slow down alternative complement activation. In this work, we characterize a PTEC-specific non-viral delivery vector composed of the cell-penetrating peptide crotamine complexed with a syndecan-1 targeting siRNA. Cell biological characterization was performed in the human PTEC HK2 cell line, using confocal microscopy, qRT-PCR, and flow cytometry. PTEC targeting in vivo was carried out in healthy mice. Crotamine/siRNA nanocomplexes are positively charged, about 100 nm in size, resistant to nuclease degradation, and showed in vitro and in vivo specificity and internalization into PTECs. The efficient suppression of syndecan-1 expression in PTECs mediated by these nanocomplexes significantly reduced properdin binding (p < 0.001), as well as the subsequent complement activation by the alternative complement pathway (p < 0.001), as observed in either normal or activated tubular conditions. To conclude, crotamine/siRNA-mediated downregulation of PTEC syndecan-1 reduced the activation of the alternative complement pathway. Therefore, we suggest that the present strategy opens new venues for targeted proximal tubular gene therapy in renal diseases.
Carboxymethyl Cellulose as a Food Emulsifier: Are Its Days Numbered?
Authors: Costa Eduardo M. , Silva Sara , Pereira Carla F. , Ribeiro Alessandra B. , Casanova Francisca , Freixo Ricardo , Pintado Manuela , Ramos Óscar L.
Published: May 2023

Carboxymethyl cellulose use in industry is ubiquitous. Though it is recognized as safe by the EFSA and FDA, newer works have raised concerns related to its safety, as in vivo studies showed evidence of gut dysbiosis associated with CMC’s presence. Herein lies the question, is CMC a gut pro-inflammatory compound? As no work addressed this question, we sought to understand whether CMC was pro-inflammatory through the immunomodulation of GI tract epithelial cells. The results showed that while CMC was not cytotoxic up to 25 mg/mL towards Caco-2, HT29-MTX and Hep G2 cells, it had an overall pro-inflammatory behavior. In a Caco-2 monolayer, CMC by itself increased IL-6, IL-8 and TNF-α secretion, with the latter increasing by 1924%, and with these increases being 9.7 times superior to the one obtained for the IL-1β pro-inflammation control. In co-culture models, an increase in secretion in the apical side, particularly for IL-6 (692% increase), was observed, and when RAW 264.7 was added, data showed a more complex scenario as stimulation of pro-inflammatory (IL-6, MCP-1 and TNF-α) and anti-inflammatory (IL-10 and IFN-β) cytokines in the basal side was observed. Considering these results, CMC may exert a pro-inflammatory effect in the intestinal lumen, and despite more studies being required, the incorporation of CMC in foodstuffs must be carefully considered in the future to minimize potential GI tract dysbiosis.
Soft Wearable Piezoresistive Sensors Based on Natural Rubber Fabricated with a Customized Vat-Based Additive Manufacturing Process
Authors: Georgopoulou Antonia , Srisawadi Sasitorn , Wiroonpochit Panithi , Clemens Frank
Published: May 2023

Piezoresistive sensors for monitoring human motions are essential for the prevention and treatment of injury. Natural rubber is a material of renewable origin that can be used for the development of soft wearable sensors. In this study, natural rubber was combined with acetylene black to develop a soft piezoresistive sensing composite for monitoring the motion of human joints. An additive manufacturing technique based on stereolithography was used, and it was seen that the sensors produced with the method could detect even small strains (<10%) successfully. With the same sensor composite fabricated by mold casting, it was not possible to detect low strains reliably. TEM microscopy revealed that the distribution of the filler was not homogeneous for the cast samples, suggesting a directionality of the conductive filler network. For the sensors fabricated through the stereolithography-based method, a homogeneous distribution could be achieved. Based on mechano-electrical characterization, it was seen that the samples produced with AM combined the ability to endure large elongations with a monotonic sensor response. Under dynamic conditions, the sensor response of the samples produced by 3D printing showed lower drift and lower signal relaxation. The piezoresistive sensors were examined for monitoring the motion of the human finger joints. By increasing the bending angle of the sensor, it was possible to increase the sensitivity of the response. With the renewable origin of natural rubber and manufacturing method, the featured sensors can expand the applicability of soft flexible electronics in biomedical applications and devices.
Development of a New Clay-Based Aerogel Composite from Ball Clay from Piauí, Brazil and Polysaccharides
Authors: Lopes Wilton C. , Brito Francisco M. , Neto Francisco E. , Araújo Alyne R. , Leite Rodolpho C. , Viana Vicente G. Freitas , Silva-Filho Edson C. , Silva Durcilene A.
Published: May 2023

The incorporation of polymeric components into aerogels based on clay produces a significant improvement in the physical and thermal properties of the aerogels. In this study, clay-based aerogels were produced from a ball clay by incorporation of angico gum and sodium alginate using a simple, ecologically acceptable mixing method and freeze-drying. The compression test showed a low density of spongy material. In addition, both the compressive strength and the Young’s modulus of elasticity of the aerogels showed a progression associated to the decrease in pH. The microstructural characteristics of the aerogels were investigated by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The chemical structure was studied by infrared spectroscopy with Fourier transform (FTIR). The TGA curves from a non-oxidizing atmosphere indicated that the clay had a mass loss of 9% above 500 °C and that due to the presence of polysaccharides, the aerogels presented a decomposition of 20% at temperatures above 260 °C. The DSC curves of the aerogels demonstrated a displacement in higher temperatures. In conclusion, the results showed that aerogels of ball clay with the incorporation of polysaccharides, which are still minimally studied, have potential application as thermal insulation considering the mechanical and thermal results obtained.
Selective Adsorption Behavior and Mechanism for Cd(II) in Aqueous Solution with a Recoverable Magnetie-Surface Ion-Imprinted Polymer
Authors: Ye Siqing , Zhang Weiye , Hu Xingliang , He Hongxing , Zhang Yi , Li Weili , Hu Guangyuan , Li Yue , Deng Xiujun
Published: May 2023

A novel recoverable magnetic Cd(II) ion-imprinted polymer was synthesized on the surface of silica-coated Fe3O4 particles via the surface imprinting technique and chemical grafting method. The resulting polymer was used as a highly efficient adsorbent for the removal of Cd(II) ions from aqueous solutions. The adsorption experiments revealed that Fe3O4@SiO2@IIP had a maximum adsorption capacity of up to 29.82 mg·g−1 for Cd(II) at an optimal pH of 6, with the adsorption equilibrium achieved within 20 min. The adsorption process followed the pseudo-second-order kinetic model and the Langmuir isotherm adsorption model. Thermodynamic studies showed that the adsorption of Cd(II) on the imprinted polymer was spontaneous and entropy-increasing. Furthermore, the Fe3O4@SiO2@IIP could rapidly achieve solid–liquid separation in the presence of an external magnetic field. More importantly, despite the poor affinity of the functional groups constructed on the polymer surface for Cd(II), we improved the specific selectivity of the imprinted adsorbent for Cd(II) through surface imprinting technology. The selective adsorption mechanism was verified by XPS and DFT theoretical calculations.
Hydrogel Applicability for the Industrial Effluent Treatment: A Systematic Review and Bibliometric Analysis
Authors: Flores-Valenzuela Luis Enrique , González-Fernández José Vulfrano , Carranza-Oropeza María Verónica
Published: May 2023

In recent decades, hydrogels, as adsorption materials, have received important attention due to their characteristics and properties, such as mechanical strength, biocompatibility, biodegradability, swellability, and stimuli sensitivity. In the actual framework of sustainable development, it has been imperative to develop practical studies of hydrogels in the treatment of actual industrial effluents. Accordingly, the current work has, as its objective, to make evident hydrogels’ applicability in the treatment of actual industrial effluents. For this purpose, a bibliometric analysis and systematic review based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method were conducted. The relevant articles were selected from the Scopus and Web of Science databases. Some important findings were that: (1) China is the leading country when it comes to hydrogel application in actual industrial effluents, (2) the motor studies are focalized on the treatment of wastewater by hydrogels, (3) the fixed-bed columns are suitable unit equipment for the treatment of industrial effluents of using hydrogels, and (4) the hydrogels show excellent adsorption capacities of ion and dye contaminants present in industrial effluents. In summary, since the implementation of sustainable development in 2015, the progress of practical hydrogel applications in the treatment of industrial effluent has been receiving more attention, and the selected studies demonstrate the implementation viability of these materials.
Synthesis of PMMA Microspheres with Tunable Diameters: Evaluation as a Template in the Synthesis of Tin Oxide Coatings
Authors: Mendoza-Castellanos José L. , Pantoja-Espinoza Juan C. , Rodríguez-Pacheco Luis C. , Paraguay-Delgado Francisco
Published: May 2023

The synthesis of polymethyl methacrylate (PMMA) spheres with different sizes has been a challenge. PMMA has promise for future applications, e.g., as a template for preparing porous oxide coatings by thermal decomposition. Different amounts of SDS as a surfactant are used as an alternative to control PMMA microsphere size through the formation of micelles. The objectives of the study were twofold: firstly, to determine the mathematical relationship between SDS concentration and PMMA sphere diameter, and secondly, to assess the efficacy of PMMA spheres as templates for SnO2 coating synthesis and their impact on porosity. The study used FTIR, TGA, and SEM techniques to analyze the PMMA samples, and SEM and TEM techniques were used for SnO2 coatings. The results showed that PMMA sphere diameter could be adjusted by varying the SDS concentration, with sizes ranging from 120 to 360 nm. The mathematical relationship between PMMA sphere diameter and SDS concentration was determined with a y = axb type equation. The porosity of SnO2 coatings was found to be dependent on the PMMA sphere diameter used as a template. The research concludes that PMMA can be used as a template to produce oxide coatings, such as SnO2, with tunable porosities.
Enhancement of Stability in n-Channel OFETs by Modulating Polymeric Dielectric
Authors: Fang Po-Hsiang , Kuo Peng-Lin , Wang Yu-Wu , Cheng Horng-Long , Chou Wei-Yang
Published: May 2023

In this study, a high-K material, aluminum oxide (AlOx), as the dielectric of organic field-effect transistors (OFETs) was used to reduce the threshold and operating voltages, while focusing on achieving high-electrical-stability OFETs and retention in OFET-based memory devices. To achieve this, we modified the gate dielectric of OFETs using polyimide (PI) with different solid contents to tune the properties and reduce the trap state density of the gate dielectric, leading to controllable stability in the N, N’-ditridecylperylene-3,4,9,10-tetracarboxylic diimide (PTCDI-C13)-based OFETs. Thus, gate field-induced stress can be compensated for by the carriers accumulated due to the dipole field created by electric dipoles within the PI layer, thereby improving the OFET’s performance and stability. Moreover, if the OFET is modified by PI with different solid contents, it can operate more stably under fixed gate bias stress over time than the device with AlOx as the dielectric layer only can. Furthermore, the OFET-based memory devices with PI film showed good memory retention and durability. In summary, we successfully fabricated a low-voltage operating and stable OFET and an organic memory device in which the memory window has potential for industrial production.
Flame Retardancy Index (FRI) for Polymer Materials Ranking
Authors: Vahabi Henri , Movahedifar Elnaz , Kandola Baljinder K. , Saeb Mohammad Reza
Published: May 2023

In 2019, we introduced Flame Retardancy Index (FRI) as a universal dimensionless index for the classification of flame-retardant polymer materials (Polymers, 2019, 11(3), 407). FRI simply takes the peak of Heat Release Rate (pHRR), Total Heat Release (THR), and Time-To-Ignition (ti) from cone calorimetry data and quantifies the flame retardancy performance of polymer composites with respect to the blank polymer (the reference sample) on a logarithmic scale, as of Poor (FRI ˂ 100), Good (100 ≤ FRI ˂ 101), or Excellent (FRI ≥ 101). Although initially applied to categorize thermoplastic composites, the versatility of FRI was later verified upon analyzing several sets of data collected from investigations/reports on thermoset composites. Over four years from the time FRI was introduced, we have adequate proof of FRI reliability for polymer materials ranking in terms of flame retardancy performance. Since the mission of FRI was to roughly classify flame-retardant polymer materials, its simplicity of usage and fast performance quantification were highly valued. Herein, we answered the question “does inclusion of additional cone calorimetry parameters, e.g., the time to pHRR (tp), affect the predictability of FRI?”. In this regard, we defined new variants to evaluate classification capability and variation interval of FRI. We also defined the Flammability Index (FI) based on Pyrolysis Combustion Flow Calorimetry (PCFC) data to invite specialists for analysis of the relationship between the FRI and FI, which may deepen our understanding of the flame retardancy mechanisms of the condensed and gas phases.
Silver Nanoparticle-Embedded Conductive Hydrogels for Electrochemical Sensing of Hydroquinone
Authors: Xu Tingting , Gao Huanli , Rojas Orlando J. , Dai Hongqi
Published: May 2023

In this work, a conductive hydrogel was successfully synthesized, taking advantage of the high number density of active amino and hydroxyl groups in carboxymethyl chitosan and sodium carboxymethyl cellulose. These biopolymers were effectively coupled via hydrogen bonding with the nitrogen atoms of the heterocyclic rings of conductive polypyrrole. The inclusion of another biobased polymer, sodium lignosulfonate (LS), was effective to achieve highly efficient adsorption and in-situ reduction of silver ions, leading to silver nanoparticles that were embedded in the hydrogel network and used to further improve the electro-catalytic efficiency of the system. Doping of the system in the pre-gelled state led to hydrogels that could be easily attached to the electrodes. The as-prepared silver nanoparticle-embedded conductive hydrogel electrode exhibited excellent electro-catalytic activity towards hydroquinone (HQ) present in a buffer solution. At the optimum conditions, the oxidation current density peak of HQ was linear over the 0.1–100 μM concentration range, with a detection limit as low as 0.12 μM (signal-to-noise of 3). The relative standard deviation of the anodic peak current intensity was 1.37% for eight different electrodes. After one week of storage in a 0.1 M Tris-HCl buffer solution at 4 °C, the anodic peak current intensity was 93.4% of the initial current intensity. In addition, this sensor showed no interference activity, while the addition of 30 μM CC, RS, or 1 mM of different inorganic ions does not have a significant impact on the test results, enabling HQ quantification in actual water samples.
Insights into Anthropogenic Micro- and Nanoplastic Accumulation in Drinking Water Sources and Their Potential Effects on Human Health
Authors: Râpă Maria , Darie-Niță Raluca Nicoleta , Matei Ecaterina , Predescu Andra-Mihaela , Berbecaru Andrei-Constantin , Predescu Cristian
Published: May 2023

Anthropogenic microplastics (MPs) and nanoplastics (NPs) are ubiquitous pollutants found in aquatic, food, soil and air environments. Recently, drinking water for human consumption has been considered a significant pathway for ingestion of such plastic pollutants. Most of the analytical methods developed for detection and identification of MPs have been established for particles with sizes > 10 μm, but new analytical approaches are required to identify NPs below 1 μm. This review aims to evaluate the most recent information on the release of MPs and NPs in water sources intended for human consumption, specifically tap water and commercial bottled water. The potential effects on human health of dermal exposure, inhalation, and ingestion of these particles were examined. Emerging technologies used to remove MPs and/or NPs from drinking water sources and their advantages and limitations were also assessed. The main findings showed that the MPs with sizes > 10 μm were completely removed from drinking water treatment plants (DWTPs). The smallest NP identified using pyrolysis–gas chromatography–mass spectrometry (Pyr-GC/MS) had a diameter of 58 nm. Contamination with MPs/NPs can occur during the distribution of tap water to consumers, as well as when opening and closing screw caps of bottled water or when using recycled plastic or glass bottles for drinking water. In conclusion, this comprehensive study emphasizes the importance of a unified approach to detect MPs and NPs in drinking water, as well as raising the awareness of regulators, policymakers and the public about the impact of these pollutants, which pose a human health risk.
Mechanical Alloying of Copper- or Iron-Based Metallic Binders for Diamond Tools
Authors: Vityaz Pyotr , Kovaliova Svetlana , Zhornik Viktor , Grigoreva Tatiana , Lyakhov Nikolay
Published: May 2023

Powder mixtures based on copper or iron are used as metal binder materials in the manufacturing of abrasive and cutting tools. This article discusses some aspects and possibilities of using a high-energy ball milling process to modify the structure and properties of Cu-Sn, Cu-Sn-Ti and Fe-Ti powders, their sintered materials and composites with diamond. The structures of powders and sintered materials, as well as the binder-to-diamond interfaces in metal matrix composites with diamond fillers, were studied by XRD analysis, scanning electron microscopy and X-ray spectroscopy. Tribological properties and thermal stability of materials in the temperature range of 250–800 °C were investigated. Various mechanisms of dispersion strengthening during the heating of sintered materials are described. It is shown that due to the grain boundary distribution of titanium, it is possible to obtain single-phase powders in the form of a supersaturated solid solution of CuSn20Ti5 and FeTi20, which ensure the formation of thermally hardened alloys with a microhardness of 357–408 HV and 561–622 HV, respectively, in the temperature range of 350–800 °C. The wear resistance of sintered powder alloys increases more than twice. Furthermore, the simultaneous enhancement in both the strength and ductility of metal–diamond titanium-containing composites is achieved through the nanostructural state and the formation of a thin layer (up to 2 μm) of titanium carbide at the interface between the metal matrix and diamond. The developed alloy shows great potential as a binder in diamond tools which are designed for machining abrasive materials.
The Racial Significance of Paul’s Clothing Metaphor (Romans 13:14; Galatians 3:27; Ephesians 4:24; Colossians 3:10)
Authors: Estrada Rodolfo Galvan
Published: May 2023

This essay proposes a new interpretation of the Pauline expression to “clothe” (ἐνδύω) oneself in Christ (Rom 13:14; Gal 3:27; Eph 4:24; Col 3:10). The phrase has been understood in terms of putting on virtues and godly characteristics. Other understandings of this phrase appear in terms of a new identity (Gal 3:27). There has been relatively limited study, however, on the significance of clothing and how different racial groups were known and characterized by their dress. Clothing was not just something that one “puts on” to protect the body from the elements or analogously understood in terms of adopting virtues. Clothing was a racial signifier, and the putting on or taking off of clothing signaled a racial transformation. The ability to “put on clothes” would have been understood in terms of the malleable nature of racial identity. By drawing on the insights of Herodotus, Aeschylus, Plutarch, and other Greek and Roman writers, this reading proposes a racial interpretation of Paul’s “clothing” phrases in Romans 13:14, Galatians 3:27, Ephesians 4:24, and Colossians 3:10. This essay explores the interpretation of these Pauline passages in contemporary scholarship, describes how the changing of clothing also signified a change of racial identity, and lastly, demonstrates how these insights can impact our understanding of the Pauline expression to “clothe oneself in Christ”.
Resonance: The Final Dissolution of Religions or the Last Stage of Secularization
Authors: Quintana Oriol , Combalia Xavier Casanovas
Published: May 2023

Secularized societies allow for all kinds of expressions of human spirituality (or lack of it). However, both the established religions and the more fluid forms of spirituality seem to leave open a specific space for the religious experience as something that cannot be met in any other form of cultural expression. Rosa’s theory of Resonance, we argue, has the potential to empty this specific space of religious experience, advancing secularization to the next level. To Rosa, a religious experience is no longer a unique form of human experience but a simple example, among others, of the variety of experiences of Resonance. Rosa, albeit inadvertently, reinforces Sloterdijk’s analysis, according to which the traditional concept of religion is a misunderstanding that can be overcome. These approaches to religion open the possibility of a third stage in the theories of secularization. In the first, the Enlightenment proclaimed that religion was to be washed away by the impulse of the immanent frame of Modernity. In the second, Taylor, Casanova, and others showed that religion never disappeared and that Modernity merely enabled religious pluralism. In the third stage of the theories of secularization, religion will be seen as a redundant cultural product.
Detection and Attribution of Greening and Land Degradation of Dryland Areas in China and America
Authors: Chen Zheng , Liu Jieyu , Hou Xintong , Fan Peiyi , Qian Zhonghua , Li Li , Zhang Zhisen , Feng Guolin , Li Bailian , Sun Guiquan
Published: May 2023

Global dryland areas are vulnerable to climate change and anthropogenic activities, making it essential to understand the primary drivers and quantify their effects on vegetation growth. In this study, we used the Time Series Segmented Residual Trends (TSS-RESTREND) method to attribute changes in vegetation to CO2, land use, climate change, and climate variability in Chinese and American dryland areas. Our analysis showed that both Chinese and American drylands have undergone a greening trend over the past four decades, with Chinese greening likely linked to climatic warming and humidification of Northwest China. Climate change was the dominant factor driving vegetation change in China, accounting for 48.3%, while CO2 fertilization was the dominant factor in American drylands, accounting for 47.9%. However, land use was the primary factor resulting in desertification in both regions. Regional analysis revealed the importance of understanding the drivers of vegetation change and land degradation in Chinese and American drylands to prevent desertification. These findings highlight the need for sustainable management practices that consider the complex interplay of climate change, land use, and vegetation growth in dryland areas.
Integration of DInSAR-PS-Stacking and SBAS-PS-InSAR Methods to Monitor Mining-Related Surface Subsidence
Authors: Chen Yuejuan , Dong Xu , Qi Yaolong , Huang Pingping , Sun Wenqing , Xu Wei , Tan Weixian , Li Xiujuan , Liu Xiaolong
Published: May 2023

Over-exploitation of coal mines leads to surface subsidence, surface cracks, collapses, landslides, and other geological disasters. Taking a mining area in Nalintaohai Town, Ejin Horo Banner, Ordos City, Inner Mongolia Autonomous Region, as an example, Sentinel-1A data from January 2018 to October 2019 were used as the data source in this study. Based on the high interference coherence of the permanent scatterer (PS) over a long period of time, the problem of the manual selection of ground control points (GCPs) affecting the monitoring results during refinement and re-flattening is solved. A DInSAR-PS-Stacking method combining the PS three-threshold method (the coherence coefficient threshold, amplitude dispersion index threshold, and deformation velocity interval) is proposed as a means to select ground control points for refinement and re-flattening, as well as a means to obtain time-series deformation by weighted stacking processing. A SBAS-PS-InSAR method combining the PS three-threshold method to select PS points as GCPs for refinement and re-flattening is also proposed. The surface deformation results monitored by the DInSAR-PS-Stacking and SBAS-PS-InSAR methods are analyzed and verified. The results show that the subsidence location, range, distribution, and space–time subsidence law of surface deformation results obtained by DInSAR-PS-Stacking, SBAS-PS-InSAR, and GPS methods are basically the same. The deformation results obtained by these two InSAR methods have a good correlation with the GPS monitoring results, and the MAE and RMSE are within the acceptable range. The error showed that the edge of the subsidence basin was small and that the center was large. Both methods were found to be able to effectively monitor the coal mine, but there were also shortcomings. DInSAR-PS-Stacking has a strong ability to monitor the settlement center. SBAS-PS-InSAR performed well in monitoring slow and small deformations, but its monitoring of the settlement center was insufficient. Considering the advantages of these two InSAR methods, we proposed fusing the time-series deformation results obtained using these two InSAR methods to allow for more reliable deformation results and to carry out settlement analysis. The results showed that the automatic two-threshold (deformation threshold and average coherence threshold) fusion was effective for monitoring and analysis, and the deformation monitoring results are in good agreement with the actual situation. The deformation information obtained by the comparison, and fusion of multiple methods can allow for better monitoring and analysis of the mining area surface deformation, and can also provide a scientific reference for mining subsidence control and early disaster warning.
FusionPillars: A 3D Object Detection Network with Cross-Fusion and Self-Fusion
Authors: Zhang Jing , Xu Da , Li Yunsong , Zhao Liping , Su Rui
Published: May 2023

In the field of unmanned systems, cameras and LiDAR are important sensors that provide complementary information. However, the question of how to effectively fuse data from two different modalities has always been a great challenge. In this paper, inspired by the idea of deep fusion, we propose a one-stage end-to-end network named FusionPillars to fuse multisensor data (namely LiDAR point cloud and camera images). It includes three branches: a point-based branch, a voxel-based branch, and an image-based branch. We design two modules to enhance the voxel-wise features in the pseudo-image: the Set Abstraction Self (SAS) fusion module and the Pseudo View Cross (PVC) fusion module. For the data from a single sensor, by considering the relationship between the point-wise and voxel-wise features, the SAS fusion module self-fuses the point-based branch and the voxel-based branch to enhance the spatial information of the pseudo-image. For the data from two sensors, through the transformation of the images’ view, the PVC fusion module introduces the RGB information as auxiliary information and cross-fuses the pseudo-image and RGB image of different scales to supplement the color information of the pseudo-image. Experimental results revealed that, compared to existing current one-stage fusion networks, FusionPillars yield superior performance, with a considerable improvement in the detection precision for small objects.
In-Situ GNSS-R and Radiometer Fusion Soil Moisture Retrieval Model Based on LSTM
Authors: Zhang Tianlong , Yang Lei , Nan Hongtao , Yin Cong , Sun Bo , Yang Dongkai , Hong Xuebao , Lopez-Baeza Ernesto
Published: May 2023

Global navigation satellite system reflectometry (GNSS-R) is a remote sensing technology of soil moisture measurement using signals of opportunity from GNSS, which has the advantages of low cost, all-weather detection, and multi-platform application. An in situ GNSS-R and radiometer fusion soil moisture retrieval model based on LSTM (long–short term memory) is proposed to improve accuracy and robustness as to the impacts of vegetation cover and soil surface roughness. The Oceanpal GNSS-R data obtained from the experimental campaign at the Valencia Anchor Station are used as the main input data, and the TB (brightness temperature) and TR (soil roughness and vegetation integrated attenuation coefficient) outputs of the ELBARA-II radiometer are used as auxiliary input data, while field measurements with a Delta-T ML2x ThetaProbe soil moisture sensor were used for reference and validation. The results show that the LSTM model can be used to retrieve soil moisture, and that it performs better in the data fusion scenario with GNSS-R and radiometer. The STD of the multi-satellite fusion model is 0.013. Among the single-satellite models, PRN13, 20, and 32 gave the best retrieval results with STD = 0.011, 0.012, and 0.007, respectively.
Nested Fabric Adaptation to New Urban Heritage Development
Authors: Shih Naai-Jung , Qiu Yu-Huan
Published: May 2023

Old urban reform usually reactivates the urban fabric in a new era of sustainable development. However, what remains of the former fabric and how it interacts with the new one often inspires curiosity. How the old residents adapt their lives to the new layout should be explored qualitatively and quantitatively. This research aimed to assess the old and new fabrics in the downtown area of Keelung, Taiwan, by considering the interactions between truncated layout, proportion, and infill orientation in the mature and immature interfaces. According to the historical reform map made in 1907, the newly constructed area occupied the old constructed area in seven downtown blocks. On average, the area composed of new buildings ranged from 135.60% to 239.20% of the old area, and the average volume of the buildings reached a maximum of 41.72 m when compared to the old buildings in place prior to the reform. It seems that the new fabric purposefully maintained the old temples at the centers of the blocks. However, the old alleys, which still remain within these blocks, have been significantly overloaded with services and have become auxiliary utility spaces for the in-block residences. With regard to the part of the fabric that was truncated or reoriented by new streets, the modification could also be easily found on the second skin. A physical model analysis used a UAV 3D cloud model and QGIS® to verify the axes, hierarchies, entrances, open spaces, and corners in the commission store block and temple blocks. We found that the 3D point model and historical maps presented a convincing explanation of the evolved fabric from the past to the present. The stepwise segmentation visualizes the enclosed block inside a block on the historical maps and according to the present sections. We found that new roles for old alleys have evolved behind the new fabric.
Tree Species Classification in Subtropical Natural Forests Using High-Resolution UAV RGB and SuperView-1 Multispectral Imageries Based on Deep Learning Network Approaches: A Case Study within the Baima Snow Mountain National Nature Reserve, China
Authors: Chen Xianggang , Shen Xin , Cao Lin
Published: May 2023

Accurate information on dominant tree species and their spatial distribution in subtropical natural forests are key ecological monitoring factors for accurately characterizing forest biodiversity, depicting the tree competition mechanism and quantitatively evaluating forest ecosystem stability. In this study, the subtropical natural forest in northwest Yunnan province of China was selected as the study area. Firstly, an object-oriented multi-resolution segmentation (MRS) algorithm was used to segment individual tree crowns from the UAV RGB imagery and satellite multispectral imagery in the forests with different densities (low (547 n/ha), middle (753 n/ha) and high (1040 n/ha)), and parameters of the MRS algorithm were tested and optimized for accurately extracting the tree crown and position information of the individual tree. Secondly, the texture metrics of the UAV RGB imagery and the spectral metrics of the satellite multispectral imagery within the individual tree crown were extracted, and the random forest algorithm and three deep learning networks constructed in this study were utilized to classify the five dominant tree species. Finally, we compared and evaluated the performance of the random forest algorithm and three deep learning networks for dominant tree species classification using the field measurement data, and the influence of the number of training samples on the accuracy of dominant tree species classification using deep learning networks was investigated. The results showed that: (1) Stand density had little influence on individual tree segmentation using the object-oriented MRS algorithm. In the forests with different stand densities, the F1 score of individual tree segmentation based on satellite multispectral imagery was 71.3–74.7%, and that based on UAV high-resolution RGB imagery was 75.4–79.2%. (2) The overall accuracy of dominant tree species classification using the light-weight network MobileNetV2 (OA = 71.11–82.22%), residual network ResNet34 (OA = 78.89–91.11%) and dense network DenseNet121 (OA = 81.11–94.44%) was higher than that of the random forest algorithm (OA = 60.00–64.44%), among which DenseNet121 had the highest overall accuracy. Texture metrics improved the overall accuracy of dominant tree species classification. (3) For the three deep learning networks, the changes in overall accuracy of dominant tree species classification influenced by the number of training samples were 2.69–4.28%.
Two New Methods Based on Implicit Expressions and Corresponding Predictor-Correctors for Gravity Anomaly Downward Continuation and Their Comparison
Authors: Zhang Chong , Qin Pengbo , Lü Qingtian , Zhou Wenna , Yan Jiayong
Published: May 2023

Downward continuation is a key technique for processing and interpreting gravity anomalies, as it has a major role in reducing values to horizontal planes and identifying small and shallow sources. However, it can be unstable and inaccurate, particularly when continuation depth increases. While the Milne and Adams–Bashforth methods based on numerical solutions of the mean-value theorem have partly addressed these problems, more accurate and realistic methods need to be presented to enhance results. To address these challenges, we present two new methods, Milne–Simpson and Adams–Bashforth–Moulton, based on implicit expressions and their predictor-correctors. We test the validity of the presented methods by applying them to synthetic models and real data, and we obtain stability, accuracy, and large depth (eight times depth intervals) downward continuation. To facilitate wider applications, we use calculated vertical derivatives (of the first order) by the integrated second vertical derivatives (ISVD) method to replace theoretical ones from forward calculations and real ones from observations, obtaining reasonable downward continuations. To further understand the effect of introduced calculation factors, we also compare previous and presented methods under different conditions, such as with purely theoretical gravity anomalies and their vertical derivatives at different heights from forward calculations, calculated gravity anomalies and their vertical derivatives at non-measurement heights above the observation by upward continuation, calculated vertical derivatives of gravity anomalies by the ISVD method at the measurement height, and noise. While the previous Adams–Bashforth method sometimes outperforms the newly presented methods, new methods of the Milne–Simpson predictor-corrector and Adams–Bashforth–Moulton predictor-corrector generally present better downward continuation results compared to previous methods.
Improving the Spatial Accuracy of UAV Platforms Using Direct Georeferencing Methods: An Application for Steep Slopes
Authors: Zeybek Mustafa , Taşkaya Selim , Elkhrachy Ismail , Tarolli Paolo
Published: May 2023

The spatial accuracy of unmanned aerial vehicles (UAVs) and the images they capture play a crucial role in the mapping process. Researchers are exploring solutions that use image-based techniques such as structure from motion (SfM) to produce topographic maps using UAVs while accessing locations with extremely high accuracy and minimal surface measurements. Advancements in technology have enabled real-time kinematic (RTK) to increase positional accuracy to 1–3 times the ground sampling distance (GSD). This paper focuses on post-processing kinematic (PPK) of positional accuracy to achieve a GSD or better. To achieve this, precise satellite orbits, clock information, and UAV global navigation satellite system observation files are utilized to calculate the camera positions with the highest positional accuracy. RTK/PPK analysis is conducted to improve the positional accuracies obtained from different flight patterns and altitudes. Data are collected at altitudes of 80 and 120 meters, resulting in GSD values of 1.87 cm/px and 3.12 cm/px, respectively. The evaluation of ground checkpoints using the proposed PPK methodology with one ground control point demonstrated root mean square error values of 2.3 cm (horizontal, nadiral) and 2.4 cm (vertical, nadiral) at an altitude of 80 m, and 1.4 cm (horizontal, oblique) and 3.2 cm (vertical, terrain-following) at an altitude of 120 m. These results suggest that the proposed methodology can achieve high positional accuracy for UAV image georeferencing. The main contribution of this paper is to evaluate the PPK approach to achieve high positional accuracy with unmanned aerial vehicles and assess the effect of different flight patterns and altitudes on the accuracy of the resulting topographic maps.
Estimation of Instantaneous Air Temperature under All-Weather Conditions Based on MODIS Products in North and Southwest China
Authors: Wang Yuanxin , Liu Jinxiu , Zhu Wenbin
Published: May 2023

Air temperature (Ta) is a common meteorological element involved in many fields, such as surface energy exchange and water circulation. Consequently, accurate Ta estimation is essential for the establishment of hydrological, climate, and environmental models. Unlike most studies concerned with the estimation of daily Ta from land surface temperature, this study focused on the estimation of instantaneous Ta from Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric profile products aboard the Terra and Aqua satellites. The applicability of various estimation methods was examined in two regions with different geomorphological and climate conditions, North and Southwest China. Specifically, the spatiotemporal trend of Ta under clear sky conditions can be reflected by the atmospheric profile extrapolation and average methods. However, the accuracy of Ta estimation was poor, with root mean square error (RMSE) ranging from 3.5 to 5.2 °C for North China and from 4.0 to 7.7 °C for Southwest China. The multiple linear regression model significantly improved the accuracy of Ta estimation by introducing auxiliary data, resulting in RMSE of 1.6 and 1.5 °C in North China and RMSE of 2.2 and 2.3 °C in Southwest China for the Terra and Aqua datasets, respectively. Since atmospheric profile products only provide information under clear sky conditions, a new multiple linear regression model was established to estimate the instantaneous Ta under cloudy sky conditions independently from atmospheric profile products, resulting in RMSE of 1.9 and 1.9 °C in North China and RMSE of 2.5 and 2.8 °C in Southwest China, for the Terra and Aqua datasets, respectively. Finally, instantaneous Ta products with high accuracy were generated for all-weather conditions in the study regions to analyze their Ta spatial patterns. The accuracy of Ta estimation varies depending on MODIS datasets, regions, elevation, and land cover types.
Joint Classification of Hyperspectral and LiDAR Data Using Binary-Tree Transformer Network
Authors: Song Huacui , Yang Yuanwei , Gao Xianjun , Zhang Maqun , Li Shaohua , Liu Bo , Wang Yanjun , Kou Yuan
Published: May 2023

The joint utilization of multi-source data is of great significance in geospatial observation applications, such as urban planning, disaster assessment, and military applications. However, this approach is confronted with challenges including inconsistent data structures, irrelevant physical properties, scarce training data, insufficient utilization of information and an imperfect feature fusion method. Therefore, this paper proposes a novel binary-tree Transformer network (BTRF-Net), which is used to fuse heterogeneous information and utilize complementarity among multi-source remote sensing data to enhance the joint classification performance of hyperspectral image (HSI) and light detection and ranging (LiDAR) data. Firstly, a hyperspectral network (HSI-Net) is employed to extract spectral and spatial features of hyperspectral images, while the elevation information of LiDAR data is extracted using the LiDAR network (LiDAR-Net). Secondly, a multi-source transformer complementor (MSTC) is designed that utilizes the complementarity and cooperation among multi-modal feature information in remote sensing images to better capture their correlation. The multi-head complementarity attention mechanism (MHCA) within this complementor can effectively capture global features and local texture information of images, hence achieving full feature fusion. Then, to fully obtain feature information of multi-source remote sensing images, this paper designs a complete binary tree structure, binary feature search tree (BFST), which fuses multi-modal features at different network levels to obtain multiple image features with stronger representation abilities, effectively enhancing the stability and robustness of the network. Finally, several groups of experiments are designed to compare and analyze the proposed BTRF-Net with traditional methods and several advanced deep learning networks using two datasets: Houston and Trento. The results show that the proposed network outperforms other state-of-the-art methods even with small training samples.
Analysis of Relationship between Grain Yield and NDVI from MODIS in the Fez-Meknes Region, Morocco
Authors: Belmahi Mohamed , Hanchane Mohamed , Krakauer Nir Y. , Kessabi Ridouane , Bouayad Hind , Mahjoub Aziz , Zouhri Driss
Published: May 2023

Exploring the relationship between cereal yield and the remotely sensed normalized difference vegetation index (NDVI) is of great importance to decision-makers and agricultural stakeholders. In this study, an approach based on the Pearson correlation coefficient and linear regression is carried out to reveal the relationship between cereal yield and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data in the Fez-Meknes region of Morocco. The results obtained show strong correlations reaching 0.70 to 0.89 between the NDVI and grain yield. The linear regression model explains 58 to 79% of the variability in yield in regional provinces marked by the importance of cereal cultivation, and 51 to 53% in the mountainous provinces with less agricultural land devoted to major cereals. The regression slopes indicate that a 0.1 increase in the NDVI results in an expected increase in grain yield of 4.9 to 8.7 quintals (q) per ha, with an average of 6.8 q/ha throughout the Fez-Meknes region. The RMSE ranges from 2.12 to 4.96 q/ha. These results are promising in terms of early yield forecasting based on MODIS-NDVI data, and consequently, in terms of grain import planning, especially since the national grain production does not cover the demand. Such remote sensing data are therefore essential for administrations that are in charge of food security decisions.
A Pattern Classification Distribution Method for Geostatistical Modeling Evaluation and Uncertainty Quantification
Authors: Zuo Chen , Li Zhuo , Dai Zhe , Wang Xuan , Wang Yue
Published: May 2023

Geological models are essential components in various applications. To generate reliable realizations, the geostatistical method focuses on reproducing spatial structures from training images (TIs). Moreover, uncertainty plays an important role in Earth systems. It is beneficial for creating an ensemble of stochastic realizations with high diversity. In this work, we applied a pattern classification distribution (PCD) method to quantitatively evaluate geostatistical modeling. First, we proposed a correlation-driven template method to capture geological patterns. According to the spatial dependency of the TI, region growing and elbow-point detection were launched to create an adaptive template. Second, a combination of clustering and classification was suggested to characterize geological realizations. Aiming at simplifying parameter specification, the program employed hierarchical clustering and decision tree to categorize geological structures. Third, we designed a stacking framework to develop the multi-grid analysis. The contribution of each grid was calculated based on the morphological characteristics of TI. Our program was extensively examined by a channel model, a 2D nonstationary flume system, 2D subglacial bed topographic models in Antarctica, and 3D sandstone models. We activated various geostatistical programs to produce realizations. The experimental results indicated that PCD is capable of addressing multiple geological categories, continuous variables, and high-dimensional structures.