bluuebunny/crossref_metadata_2025 huggingface dataset:
Design, Fabrication and Validation of Mixed Order Distributed Feed-Back Organic Diode Laser Cavity
Authors: Ouirimi Amani , Chime Alex Chamberlain , Loganathan Nixson , Chakaroun Mahmoud , Lenstra Daan , Fischer Alexis P. A.
Published: June 2023

In the context of the quest for the organic laser diode, we address a key challenge to design and fabricate high-quality factor cavities compatible with electrical excitation of organic semiconductors. More precisely, we present the design of DFB micro-cavities for integration in organic laser diodes and their validation under optical pumping. To design high-quality factor mixed-order DFB micro-cavities, we consider the half- and quarter-wavelength multilayered system and use the optical waveguide analysis to quantify the effective indices of the high and low indices, and the matrix transfer method to calculate the reflectances. Matrices of DFB micro-cavities made from different doses and different grating periods were fabricated. We then identified those showing laser emission under optical pumping as an indication of optimal matching of their resonance wavelength with respect to the electroluminescence peak of the organic gain material. Potential applications of organic laser diodes deal with light communication, spectroscopy, sensors, and other applications where heterogenous integration is important.
Arbitrary Time Shaping of Broadband Low-Coherence Light Based on Optical Parametric Amplification
Authors: Wang Yue , Wang Xiaochao , Sun Meizhi , Liang Xiao , Wei Hui , Fan Wei
Published: June 2023

Laser–plasma interactions (LPIs) hinder the interaction of high-energy laser pulses with targets. The use of broadband low-coherence light has been proposed to reduce the impact of LPIs. In this study, to improve the time–frequency characteristics of broadband low-coherence optical seeds, we proposed an arbitrary time-shaping technique scheme based on optical parametric amplification (OPA) that differs from traditional arbitrary time shaping. The shaping process and output characteristics were analyzed in detail. The theoretical and experimental results show that an arbitrary time-shaping pulse output with a large time-shaping contrast, fast-rising edge, and wide spectral width can be obtained. The time shaping contrast of the shaped pulse can be >300:1, and the spectral width is ~40 nm. The output time waveform is smoother than in traditional schemes, and the noise-like modulation is approximately 4% (approximately equal to the unshaped initial amplified spontaneous emission source). The arbitrary time-shaping scheme based on OPA provides a viable solution for the temporal waveform shaping of broadband low-coherence light.
Effects of Engaging Older Adults in Technology-Based Dance Programs
Authors: Zilidou Vasiliki I. , Bamidis Panagiotis D.
Published: June 2023

Functionality is a crucial aspect of aging that is vital to one’s health and well-being. Older adults often struggle with mobility issues, which increases their risk of injury from falls and other problems. Dancing has the potential to be a physically stimulating activity that may be tailored to older individuals’ ages, physical conditions, and cultural preferences. The study aimed to determine whether dancing programs can improve older adults’ physical and mental health by using technology. Sixty women were divided into two groups at random: a dance group (N = 33; mean age 62.24) and a dance group using technology (N = 27, mean age 67.37). The intervention lasted six months and was performed twice a week for 75-min sessions. Dances were chosen from all over Greece. Participants’ physical and cognitive status was evaluated before and after the intervention. The results show that the dance group improved balance (p = 0.001), lower body strength (p = 0.006) and aerobic capacity (p = 0.006), while the dance group with the use of technology shower greater improvement in the same tests (p = 0.002, p < 0.0001 and p < 0.0001). Both groups improved on walking balance and danger of falling (p < 0.0001). Depression (p = 0.007) and sociability (p = 0.001) significantly improved in the dance group. Dance, an enjoyable activity, contributes to the well-being of older adults by maintaining their physical status and functional capacity at acceptable levels.
Mutual Effect of Gypsum and Potassium on Nutrient Productivity in the Alfalfa–Grass Sward—A Case Study
Authors: Zielewicz Waldemar , Grzebisz Witold , Biber Maria
Published: June 2023

It was assumed that the production of alfalfa in soils naturally poor in available nutrients, such as potassium (K) and calcium (Ca), depends on the use of fertilizers. This hypothesis was validated in an experiment with an alfalfa–grass mixture carried out in 2012, 2013 and 2014 on soil formed from loamy sand that had a low content of available Ca and K. The two-factor experiment consisted of two levels of applied gypsum as a source of Ca (0, 500 kg ha−1) and five levels of PK fertilizers (absolute control, P60K0, P60K30, P60K60 and P60K120). The total yield of the sward was determined by the main seasons of alfalfa–grass sward use. Gypsum application increased the yield by 1.0 t ha−1. The highest yield of 14.9 t ha−1 was obtained on the plot fertilized with P60K120. Based on the nutrient content in the sward, it was shown that the main yield predictor was the content of K in the first cut of sward use. The reliable yield predictors, based on the total accumulation of nutrients in the sward, turned out to be K, Mg and Fe. The nutritional quality of the alfalfa–grass fodder, based on the K/Ca + Mg ratio, depended mainly on the season of the sward use, which was substantially deteriorated by the K fertilizer. Gypsum did not control this process. The productivity of the nutrients taken up by the sward depended on the accumulated K. Its yield-forming effect was significantly limited by manganese deficiency. The use of gypsum positively affected the uptake of micronutrients, consequently increasing their unit productivity, especially of manganese. Optimization of the production of alfalfa–grass mixtures in soils poor in basic nutrients requires micronutrients to be taken into account. Their uptake by plants can be limited by high doses of basic fertilizers.
Metagenomic Study of Fungal Microbial Communities in Two PDO Somontano Vineyards (Huesca, Spain): Effects of Age, Plant Genotype, and Initial Phytosanitary Status on the Priming and Selection of their Associated Microorganisms
Authors: Langa-Lomba Natalia , Grimplet Jerome , Sánchez-Hernández Eva , Martín-Ramos Pablo , Casanova-Gascón José , Julián-Lagunas Carmen , González-García Vicente
Published: June 2023

The study of microbial communities associated with different plants of agronomic interest has allowed, in recent years, to answer a number of questions related to the role and influence of certain microbes in key aspects of their autoecology, such as improving the adaptability of the plant host to different abiotic or biotic stresses. In this study, we present the results of the characterization, through both high-throughput sequencing and classical microbiological methods, of the fungal microbial communities associated with grapevine plants in two vineyards of different ages and plant genotypes located in the same biogeographical unit. The study is configured as an approximation to the empirical demonstration of the concept of “microbial priming” by analyzing the alpha- and beta-diversity present in plants from two plots subjected to the same bioclimatic regime to detect differences in the structure and taxonomic composition of the populations. The results were compared with the inventories of fungal diversity obtained by culture-dependent methods to establish, where appropriate, correlations between both microbial communities. Metagenomic data showed a differential enrichment of the microbial communities in the two vineyards studied, including the populations of plant pathogens. This is tentatively explained due to factors such as the different time of exposure to microbial infection, different plant genotype, and different starting phytosanitary situation. Thus, results suggest that each plant genotype recruits differential fungal communities and presents different profiles of associated potential microbial antagonists or communities of pathogenic species.
Plants’ Response Mechanisms to Salinity Stress
Authors: Balasubramaniam Thuvaraki , Shen Guoxin , Esmaeili Nardana , Zhang Hong
Published: June 2023

Soil salinization is a severe abiotic stress that negatively affects plant growth and development, leading to physiological abnormalities and ultimately threatening global food security. The condition arises from excessive salt accumulation in the soil, primarily due to anthropogenic activities such as irrigation, improper land uses, and overfertilization. The presence of Na⁺, Cl−, and other related ions in the soil above normal levels can disrupt plant cellular functions and lead to alterations in essential metabolic processes such as seed germination and photosynthesis, causing severe damage to plant tissues and even plant death in the worst circumstances. To counteract the effects of salt stress, plants have developed various mechanisms, including modulating ion homeostasis, ion compartmentalization and export, and the biosynthesis of osmoprotectants. Recent advances in genomic and proteomic technologies have enabled the identification of genes and proteins involved in plant salt-tolerance mechanisms. This review provides a short overview of the impact of salinity stress on plants and the underlying mechanisms of salt-stress tolerance, particularly the functions of salt-stress-responsive genes associated with these mechanisms. This review aims at summarizing recent advances in our understanding of salt-stress tolerance mechanisms, providing the key background knowledge for improving crops’ salt tolerance, which could contribute to the yield and quality enhancement in major crops grown under saline conditions or in arid and semiarid regions of the world.
Pollen Morphology of Convolvulaceae from Southeastern Amazonian Cangas and Its Relevance for Interaction Networks and Paleoenvironmental Studies
Authors: Romeiro Luiza de Araújo , da Silva Edilson Freitas , Vasconcelos Liziane Vilela , Lopes Karen da Silva , Carreira Léa Maria Medeiros , Guimarães José Tasso Felix
Published: June 2023

Serra dos Carajás harbors a unique open plant community in Amazonia, known as canga vegetation, with several endemic species coexisting with the potential threat of large-scale iron ore mining. In this sense, Convolvulaceae occur in a wide variety of canga geoenvironments with multiple flower visitors, but the scarcity of data on its pollen morphology prevents the correct association between Convolvulaceae species with floral visitors, as well as the precise identification of their habitats throughout the Quaternary. Therefore, this study aims to contribute to the taxonomic knowledge and refinement of the identification of insect-plant networks of endangered plants, including Ipomoea cavalcantei. Pollen grains were examined by light and scanning electron microscopy (LM and SEM, respectively), and the morphological parameters obtained were statistically analyzed using principal component analysis. Therefore, all species were differentiated based on aperture types and exine ornamentation. The set of morphological characters indicated that echinae morphology, easily identified under LM, was effective for the identification of Ipomoea species. This work represents the first robust pollen database for a precise identification at the species level of Convolvulaceae from southeastern Amazonian cangas.
3D-Printed PLA Scaffold with Fibronectin Enhances In Vitro Osteogenesis
Authors: Salamanca Eisner , Choy Cheuk Sing , Aung Lwin Moe , Tsao Ting-Chia , Wang Pin-Han , Lin Wei-An , Wu Yi-Fan , Chang Wei-Jen
Published: June 2023

Background: Tricalcium phosphate (TCP, Molecular formula: Ca3(PO4)2) is a hydrophilic bone graft biomaterial extensively used for guided bone regeneration (GBR). However, few studies have investigated 3D-printed polylactic acid (PLA) combined with the osteo-inductive molecule fibronectin (FN) for enhanced osteoblast performance in vitro, and specialized bone defect treatments. Aim: This study evaluated PLA properties and efficacy following glow discharge plasma (GDP) treatment and FN sputtering for fused deposition modeling (FDM) 3D printed PLA alloplastic bone grafts. Methods: 3D trabecular bone scaffolds (8 × 1 mm) were printed by the 3D printer (XYZ printing, Inc. 3D printer da Vinci Jr. 1.0 3-in-1). After printing PLA scaffolds, additional groups for FN grafting were continually prepared with GDP treatment. Material characterization and biocompatibility evaluations were investigated at 1, 3 and 5 days. Results: SEM images showed the human bone mimicking patterns, and EDS illustrated the increased C and O after fibronectin grafting, XPS and FTIR results together confirmed the presence of FN within PLA material. Degradation increased after 150 days due to FN presence. 3D immunofluorescence at 24 h demonstrated better cell spreading, and MTT assay results showed the highest proliferation with PLA and FN (p < 0.001). Cells cultured on the materials exhibited similar alkaline phosphatase (ALP) production. Relative quantitative polymerase chain reaction (qPCR) at 1 and 5 days revealed a mixed osteoblast gene expression pattern. Conclusion: In vitro observations over a period of five days, it was clear that PLA/FN 3D-printed alloplastic bone graft was more favorable for osteogenesis than PLA alone, thereby demonstrating great potential for applications in customized bone regeneration.
Intelligent Polymers for Multi-Functional Applications: Mechanical and Electrical Aspects
Authors: Sheikhi Mohammad Rauf , Gürgen Selim
Published: June 2023

In this study, we fabricated an intelligent material, shear stiffening polymer (SSP), and reinforced it with carbon nanotube (CNT) fillers to obtain intelligent mechanical and electrical properties. The SSP was enhanced with multi-functional behavior, such as electrical conductivity and stiffening texture. Various amounts of CNT fillers were distributed in this intelligent polymer up to a loading rate of 3.5 wt%. The mechanical and electrical aspects of the materials were investigated. Regarding the mechanical properties, dynamic mechanical analysis was carried out, as well as conducting shape stability and free-fall tests. Viscoelastic behavior was investigated in the dynamic mechanical analysis, whereas cold-flowing and dynamic stiffening responses were studied in shape stability and free-fall tests, respectively. On the other hand, electrical resistance measurements were carried out to understand the conductive behavior of the polymers of the electrical properties. Based on these results, CNT fillers enhance the elastic nature of the SSP while initiating the stiffening behavior at lower frequencies. Moreover, CNT fillers provide higher shape stability, hindering the cold flow in the material. Lastly, SSP gained an electrically conductive nature from the CNT fillers.
Tailored Dynamic Viscoelasticity of Polyurethanes Based on Different Diols
Authors: Wang Jiadong , Wang Min , Xu Chenxin , Han Yang , Qin Xuan , Zhang Liqun
Published: June 2023

The development of damping and tire materials has led to a growing need to customize the dynamic viscoelasticity of polymers. In the case of polyurethane (PU), which possesses a designable molecular structure, the desired dynamic viscoelasticity can be achieved by carefully selecting flexible soft segments and employing chain extenders with diverse chemical structures. This process involves fine-tuning the molecular structure and optimizing the degree of micro-phase separation. It is worth noting that the temperature at which the loss peak occurs increases as the soft segment structure becomes more rigid. By incorporating soft segments with varying degrees of flexibility, the loss peak temperature can be adjusted within a broad range, from −50 °C to 14 °C. Furthermore, when the molecular structure of the chain extender becomes more regular, it enhances interaction between the soft and hard segments, leading to a higher degree of micro-phase separation. This phenomenon is evident from the increased percentage of hydrogen-bonding carbonyl, a lower loss peak temperature, and a higher modulus. By modifying the molecular weight of the chain extender, we can achieve precise control over the loss peak temperature, allowing us to regulate it within the range of −1 °C and 13 °C. To summarize, our research presents a novel approach for tailoring the dynamic viscoelasticity of PU materials and thus offers a new avenue for further exploration in this field.
Valorization of Honduran Agro-Food Waste to Produce Bioplastics
Authors: Castro-Criado Daniel , Rivera-Flores Octavio , Abdullah Johar Amin Ahmed , Castro-Osorto Elia , Alonso-González María , Ramos-Casco Lucy , Perez-Puyana Víctor M. , Sánchez-Barahona Marlon , Sánchez-Cid Pablo , Jiménez-Rosado Mercedes , Romero Alberto
Published: June 2023

The development of biodegradable plastics and eco-friendly biomaterials derived from renewable resources is crucial for reducing environmental damage. Agro-industrial waste and rejected food can be polymerized into bioplastics, offering a sustainable solution. Bioplastics find use in various industries, including for food, cosmetics, and the biomedical sector. This research investigated the fabrication and characterization of bioplastics using three types of Honduran agro-wastes: taro, yucca, and banana. The agro-wastes were stabilized and characterized (physicochemically and thermically). Taro flour presented the highest protein content (around 4.7%) and banana flour showed the highest moisture content (around 2%). Furthermore, bioplastics were produced and characterized (mechanically and functionally). Banana bioplastics had the best mechanical properties, with a Young’s modulus around 300 MPa, while taro bioplastics had the highest water-uptake capacity (200%). In general, the results showed the potential of these Honduran agro-wastes for producing bioplastics with different characteristics that could add value to these wastes, promoting the circular economy.
Development of an All-Marine 3D Printed Bioactive Hydrogel Dressing for Treatment of Hard-to-Heal Wounds
Authors: Stenlund Patrik , Enstedt Linnea , Gilljam Karin Margaretha , Standoft Simon , Ahlinder Astrid , Lundin Johnson Maria , Lund Henrik , Millqvist Fureby Anna , Berglin Mattias
Published: June 2023

Current standard wound care involves dressings that provide moisture and protection; however, dressings providing active healing are still scarce and expensive. We aimed to develop an ecologically sustainable 3D printed bioactive hydrogel-based topical wound dressing targeting healing of hard-to-heal wounds, such as chronic or burn wounds, which are low on exudate. To this end, we developed a formulation composed of renewable marine components; purified extract from unfertilized salmon roe (heat-treated X, HTX), alginate from brown seaweed, and nanocellulose from tunicates. HTX is believed to facilitate the wound healing process. The components were successfully formulated into a 3D printable ink that was used to create a hydrogel lattice structure. The 3D printed hydrogel showed a HTX release profile enhancing pro-collagen I alpha 1 production in cell culture with potential of promoting wound closure rates. The dressing has recently been tested on burn wounds in Göttingen minipigs and shows accelerated wound closure and reduced inflammation. This paper describes the dressings development, mechanical properties, bioactivity, and safety.
Design and Synthesis of Porous Organic Polymers: Promising Catalysts for Lignocellulose Conversion to 5-Hydroxymethylfurfural and Derivates
Authors: Yang Lei , Shao Lishu , Wu Zhiping , Zhan Peng , Zhang Lin
Published: June 2023

In the face of the current energy and environmental problems, the full use of biomass resources instead of fossil energy to produce a series of high-value chemicals has great application prospects. 5-hydroxymethylfurfural (HMF), which can be synthesized from lignocellulose as a raw material, is an important biological platform molecule. Its preparation and the catalytic oxidation of subsequent products have important research significance and practical value. In the actual production process, porous organic polymer (POP) catalysts are highly suitable for biomass catalytic conversion due to their high efficiency, low cost, good designability, and environmentally friendly features. Here, we briefly describe the application of various types of POPs (including COFs, PAFs, HCPs, and CMPs) in the preparation and catalytic conversion of HMF from lignocellulosic biomass and analyze the influence of the structural properties of catalysts on the catalytic performance. Finally, we summarize some challenges that POPs catalysts face in biomass catalytic conversion and prospect the important research directions in the future. This review provides valuable references for the efficient conversion of biomass resources into high-value chemicals in practical applications.
Chameleon-Inspired Mechanochromic Photonic Elastomer with Brilliant Structural Color and Stable Optical Response for Human Motion Visualization
Authors: Zhao Yanbo , Zhao Kai , Yu Zhumin , Ye Changqing
Published: June 2023

Flexible and stretchable electronic devices are indispensable parts of wearable devices. However, these electronics employ electrical transducing modes and lack the ability to visually respond to external stimuli, restricting their versatile application in the visualized human–machine interaction. Inspired by the color variation of chameleons’ skin, we developed a series of novel mechanochromic photonic elastomers (PEs) with brilliant structural colors and a stable optical response. Typically, these PEs with a sandwich structure were prepared by embedding PS@SiO2 photonic crystals (PCs)within the polydimethylsiloxane (PDMS) elastomer. Benefiting from this structure, these PEs exhibit not only bright structural colors, but also superior structural integrity. Notably, they possess excellent mechanochromism through lattice spacing regulation, and their optical responses are stably maintained even when suffering from 100 stretching–releasing cycles, showing superior stability and reliability and excellent durability. Moreover, a variety of patterned PEs were successfully obtained through a facile mask method, which provides great inspiration to create intelligent patterns and displays. Based on these merits, such PEs can be utilized as visualized wearable devices for detecting various human joint movements in real time. This work offers a new strategy for realizing visualized interactions based on PEs, showing huge application prospects in photonic skins, soft robotics, and human–machine interactions.
Impact of the New Energy Context on the Feasibility of Solar Water Heating Systems in the Agri-Food Industry
Authors: Perdigones Alicia , Baptista Fátima , García José L. , Benavente Rosa M. , Mazarrón Fernando R.
Published: June 2023

The new energy context since 2021 has led to dramatic increases in the energy bills of agribusinesses, affecting the price of foodstuffs. A considerable part of energy consumption is due to the heating of water at high temperatures. The present study analyzed the feasibility of using a Solar Water Heating System (SWHS) with an evacuated tube collector. In particular, the required sizing changes, potential savings and cost-effectiveness were analyzed. The results show that the new energy context makes the SWHS investment highly attractive: a payback of less than 4 years in most of the scenarios analyzed; energy savings of more than 60% in the scenarios with higher irradiation; a reduction in total energy expenditure of more than 50% in the favorable scenarios close to the current reality. The new context especially favors cold and temperate climates, with very sharp drops in payback compared to the previous situation. To achieve these values, it is necessary to design an optimized sizing of the SWHS, reducing the risk of future variations in the price of energy. The results of the study should serve as a reference for decision making in the agroindustrial sector to reduce the energy bill and strategic dependence on fossil fuels from third countries.
“It’s Not a One-Time Conversation”: Australian Parental Views on Supporting Young People in Relation to Pornography Exposure
Authors: Burke Sally , Purvis Mayumi , Sandiford Carol , Klettke Bianca
Published: June 2023

While pornography provides opportunities for sexual exploration for young people, early and easy access also has possible negative implications for young people’s behavioural and sexual development. Parental responsibilities concerning their children’s consumption of pornography are largely misunderstood. This study explored parental experiences and beliefs about pornography education for young people using a qualitative study (n = 8, 6 females, 2 males). Interview data were analysed using a reflexive thematic approach. Results indicated that parents have concerns about the ease of access to pornography and the unmediated ideas it presents. Additionally, parents believe they have a responsibility to educate young people about pornography through having open and honest conversations and providing supervision. Further, parents believe that schools should be doing more to educate young people about pornography. This study extends upon current literature by suggesting that although parents feel well-equipped to communicate with and educate young people about pornography consumption, they lack confidence in their capacities to do this.
Assessment of Pollen Representation in NW Italy (Liguria and Piedmont)
Authors: Attolini Davide , Ciani Francesco , Guido Maria Angela , Montanari Carlo
Published: June 2023

This research focuses on the recent pollen image of several vegetation types in NW Italy. In 201 arboreal, shrubby, and herbaceous plant populations, pollen samples were taken from moss polsters, and the corresponding vegetation was recorded using the phytosociological method. Since studies on recent pollen rain in the Mediterranean mountains and coast are rare, this research aims to provide new data and tools to better interpret fossil pollen spectra. Pollen analysis provided data for the comparison between surface spectra and vegetation. Davis indices, fidelity, dispersion, and the relation with vegetation data were calculated for each taxon, and PCA was carried out. Most vegetation types are identifiable through the taxa dominating the pollen spectra, as frequently happens in woodlands (e.g., beech woods, chestnut woods, etc.). Characterizing shrubland and certain tree-dominated vegetation types (e.g., Larix forests) through pollen data is more complex. In this regard, Davis indices are particularly useful for identifying pollen/plant association, over- and underrepresentation of pollen, and taxa indicating vegetation types. Pollen threshold values were calculated which allow the assessment of the local presence of a plant. Overall, the achieved results partially confirm those of previous research carried out in the region, greatly expanding the comparisons between several different plant communities and the database in view of future sharing through the EMPD.
Correction: Niu et al. SMNet: Symmetric Multi-Task Network for Semantic Change Detection in Remote Sensing Images Based on CNN and Transformer. Remote Sens. 2022, 15, 949
Authors: Niu Yiting , Guo Haitao , Lu Jun , Ding Lei , Yu Donghang
Published: June 2023

In the original publication [...]
A Feature-Level Point Cloud Fusion Method for Timber Volume of Forest Stands Estimation
Authors: Guo Lijie , Wu Yanjie , Deng Lei , Hou Peng , Zhai Jun , Chen Yan
Published: June 2023

Accurate diameter at breast height (DBH) and tree height (H) information can be acquired through terrestrial laser scanning (TLS) and airborne LiDAR scanner (ALS) point cloud, respectively. To utilize these two features simultaneously but avoid the difficulties of point cloud fusion, such as technical complexity and time-consuming and laborious efforts, a feature-level point cloud fusion method (FFATTe) is proposed in this paper. Firstly, the TLS and ALS point cloud data in a plot are georeferenced by differential global navigation and positioning system (DGNSS) technology. Secondly, point cloud processing and feature extraction are performed for the georeferenced TLS and ALS to form feature datasets, respectively. Thirdly, the feature-level fusion of LiDAR data from different data sources is realized through spatial join according to the tree trunk location obtained from TLS and ALS, that is, the tally can be implemented at a plot. Finally, the individual tree parameters are optimized based on the tally results and fed into the binary volume model to estimate the total volume (TVS) in a large area (whole study area). The results show that the georeferenced ALS and TLS point cloud data using DGNSS RTK/PPK technology can achieve coarse registration (mean distance ≈ 40 cm), which meets the accuracy requirements for feature-level point cloud fusion. By feature-level fusion of the two point cloud data, the tally can be achieved quickly and accurately in the plot. The proposed FFATTe method achieves high accuracy (with error of 3.09%) due to its advantages of combining different LiDAR data from different sources in a simple way, and it has strong operability when acquiring TVS over large areas.
The Correction Method of Water and Fresnel Reflection Coefficient for Soil Moisture Retrieved by CYGNSS
Authors: Wang Qi , Sun Jiaojiao , Chang Xin , Jin Taoyong , Shang Jinguang , Liu Zhiyong
Published: June 2023

Spaceborne GNSS-R technology is a new remote sensing method for soil moisture monitoring. Focusing on the significant influence of water on the surface reflectivity of CYGNSS, this paper improved the removal method of water influence according to the spatial resolution of CYGNSS data. Due to the disturbance effect of the incident angle, microwave frequency and soil type on the Fresnel reflection coefficient in surface reflectivity, a normalization method of Fresnel reflection coefficient was proposed after analyzing the data characteristics of variables in the Fresnel reflection coefficient. Finally, combined with the soil moisture retrieval method of linear equation, the accuracy was compared and verified by using measured data, SMAP products and official CYGNSS products. The results indicate that the normalization method of the Fresnel reflection coefficient could effectively reduce the influence of relevant parameters on the Fresnel reflection coefficient, but the normalization effect became worse at large incident angles (greater than 65°). Compared with the official CYGNSS product, the retrieval accuracy of optimized soil moisture was improved by 10%. The method proposed in this paper will play an important reference role in the study of soil moisture retrieval using spaceborne GNSS-R data.
Inverse Scattering Series Internal Multiple Attenuation in the Common-Midpoint Domain
Authors: Sun Jian , Innanen Kristopher A. , Niu Zhan , Eaid Matthew V.
Published: June 2023

Internal multiple prediction remains a high-priority problem in seismic data processing, such as subsurface imaging and quantitative amplitude analysis and inversion, particularly in the common-midpoint (CMP) gathers, which contain multicoverage reflection information of the subsurface. Internal multiples, generated by unknown reflectors in complex environments, can be reconstructed with certain combinations of seismic reflection events using the inverse scattering series internal multiple prediction algorithm, which is usually applied to shot records in source–receiver coordinates. The computational overhead is one of the major challenges limiting the strength of the multidimensional implementation of the prediction algorithm, even in the coupled plane-wave domain. In this paper, we first comprehensively review the plane-wave domain inverse scattering series internal multiple prediction algorithm, and we propose a new scheme of achieving 2D multiple attenuation using a 1.5D prediction algorithm in the CMP domain, which significantly reduces the computational burden. Moreover, we quantify the difference in behavior of the 1.5D prediction algorithm for the shot/receiver and the CMP gathers on tilted strata. Numerical analysis of prediction errors shows that the 1.5D algorithm is more capable of handling dipping generators in the CMP domain than in the shot/receiver gathers, and it is able to predict the accredited traveltimes of internal multiples caused by dipping reflectors with small inclinations. For more complex cases with large inclination, using the 1.5D prediction algorithm, internal multiple predictions fail both in the CMP domain and in the shot/receiver gathers, which require the full 2D prediction algorithm. To attenuate internal multiples in the CMP gathers generated by large-dipping strata, a modified version is proposed based on the full 2D plane-wave domain internal multiple prediction algorithm. The results show that the traveltimes of internal multiples caused by dipping generators seen in the simple benchmark example are correctly predicted in the CMP domain using the modified 2D prediction algorithm.
Correction: Wang et al. Increased Compound Droughts and Heatwaves in a Double Pack in Central Asia. Remote Sens. 2022, 14, 2959
Authors: Wang Chuan , Li Zhi , Chen Yaning , Li Yupeng , Liu Xigang , Hou Yifeng , Wang Xuechun , Kulaixi Zulipiya , Sun Fan
Published: June 2023

In the original article [...]
Snow Cover Mapping Based on SNPP-VIIRS Day/Night Band: A Case Study in Xinjiang, China
Authors: Chen Baoying , Zhang Xianfeng , Ren Miao , Chen Xiao , Cheng Junyi
Published: June 2023

Detailed snow cover maps are essential for estimating the earth’s energy balance and hydrological cycle. Mapping the snow cover across spatially extensive and topographically complex areas with less or no cloud obscuration is challenging, but the SNPP-VIIRS Day/Night Band (DNB) nighttime light data offers a potential solution. This paper aims to map snow cover distribution at 750 m resolution across the diverse 1,664,900 km2 of Xinjiang, China, based on SNPP-VIIRS DNB radiance. We implemented a swarm intelligent optimization technique Krill Herd algorithm, which finds the optimal threshold value by taking Otsu’s method as the objective function. We derived SNPP-VIIRS DNB snow maps of 14 consecutive scenes in December 2021, compared our snow-covered area estimations with those from MODIS and AMSR2 standard snow cover products, and generated composite snow maps by merging MODIS and SNPP-VIIRS DNB data. Results show that SNPP-VIIRS DNB snow maps are capable of providing reliable snow cover maps superior to MODIS and AMSR2, with an overall accuracy level of 84.66%. The composite snow maps at 500 m spatial resolution provided 55.85% more information on snow cover distribution than standard MODIS products and achieved an overall accuracy of 84.69%. Our study demonstrated the feasibility of snow cover detection in Xinjiang based on SNPP-VIIRS DNB, which can serve as a supplementary dataset for MODIS estimations where clouded pixels are present.
Adversarial Robustness Enhancement of UAV-Oriented Automatic Image Recognition Based on Deep Ensemble Models
Authors: Lu Zihao , Sun Hao , Xu Yanjie
Published: June 2023

Deep neural networks (DNNs) have been widely utilized in automatic visual navigation and recognition on modern unmanned aerial vehicles (UAVs), achieving state-of-the-art performances. However, DNN-based visual recognition systems on UAVs show serious vulnerability to adversarial camouflage patterns on targets and well-designed imperceptible perturbations in real-time images, which poses a threat to safety-related applications. Considering a scenario in which a UAV is suffering from adversarial attack, in this paper, we investigate and construct two ensemble approaches with CNN and transformer for both proactive (i.e., generate robust models) and reactive (i.e., adversarial detection) adversarial defense. They are expected to be secure under attack and adapt to the resource-limited environment on UAVs. Specifically, the probability distributions of output layers from base DNN models in the ensemble are combined in the proactive defense, which mainly exploits the weak adversarial transferability between the CNN and transformer. For the reactive defense, we integrate the scoring functions of several adversarial detectors with the hidden features and average the output confidence scores from ResNets and ViTs as a second integration. To verify their effectiveness in the recognition task of remote sensing images, we conduct experiments on both optical and synthetic aperture radar (SAR) datasets. We find that the ensemble model in proactive defense performs as well as three popular counterparts, and both of the ensemble approaches can achieve much more satisfactory results than a single base model/detector, which effectively alleviates adversarial vulnerability without extra re-training. In addition, we establish a one-stop platform for conveniently evaluating adversarial robustness and performing defense on recognition models called AREP-RSIs, which is beneficial for the future research of the remote sensing field.
Spatial and Temporal Characteristics of Drought Events in Southwest China over the Past 120 Years
Authors: Wang Ying , Wang Yuanmou , Chen Yanan , Chen Huan , Li Xingting , Ding Zhi , Han Xujun , Tang Xuguang
Published: June 2023

Global climate change, especially extreme drought events, presents a complicated challenge to humanity and Earth’s system in the 21st century. As an extremely important carbon sink region in China, Southwest China has encountered frequent drought disasters in recent decades. It is critical to explore the frequency, duration, severity, and other associated characteristics of drought events as well as their spatial and temporal patterns in the region from a long-term perspective. In this study, we used the latest dataset from the Spanish National Research Council (CSIC) between 1901 and 2018 to extract all drought events by calculating the standardized anomaly of the Standardized Precipitation Evapotranspiration Index (SPEI). Theil–Sen median trend analysis, the Mann–Kendall test, and the moving t-test were used to reveal the spatial trend and mutation point of drought severity. The results showed that (1) The standardized anomaly of the 3-month SPEI can accurately identify drought events in Southwest China. In total, 72 drought events occurred during this period, of which the consecutive drought in autumn, winter, and spring from 2009 to 2010 lasted the longest, having the most substantial severity and the most extensive damage range. (2) Drought events mainly started in spring and early summer and ended in autumn and winter. The distribution of drought was the most expansive and the drought severity was the most serious in September. (3) In terms of spatial pattern, Guangxi has the highest frequency of drought events, with some areas experiencing up to 100 events. The average duration of drought events ranged between 3.5 and 5.5 months, with most lasting for 4–5 months. The most severe drought areas are mainly concentrated in southern Sichuan and western Yunnan. Overall, the severity of drought events in the west were generally higher compared to that in the east. (4) Over the past 120 years, most of the region (82.46%) showed an increasing trend in drought severity, with a slope of up to −0.01. About 15.12% of the areas exhibited a significant drying trend (p < 0.05), particularly in southern Sichuan, eastern Guizhou, and northern and southern Yunnan. Such analyses can serve as a scientific foundation for developing drought prevention and mitigation measures as well as exploring how drought events affect the structure and function of terrestrial ecosystems in Southwest China.
Coseismic Source Model of the February 2023 Mw 6.8 Tajikistan Earthquake from Sentinel-1A InSAR Observations and Its Associated Earthquake Hazard
Authors: Shi Ying , Wang Yongzhe , Bian Yinju
Published: June 2023

On 23 February 2023, an Mw 6.8 earthquake struck the border of Tajikistan and Xinjiang China, the source mechanism remains controversial according to different seismic inversions. To better comprehend the source characteristics and the surface deformation pattern, we used the ascending and descending orbital Sentinel-1A SAR data to obtain the coseismic deformation of this earthquake based on the traditional two-pass differential interferometric synthetic aperture radar (InSAR). The source model is inverted from the InSAR coseismic deformation results. The possible Coulomb Failure Stress (CFS) transfer is analyzed based on the preferred source model. The results illustrate that the earthquake ruptured a blind left-lateral strike-slip fault of strike 28.1° with a maximum slip of 1.53 m and the total geodetic moment is 1.99 × 1019 N·m (Mw 6.83). The strike direction and the fault characteristics suggest the Seismogenic fault is a secondary fault of the Sarez–Karakul Fault System. The 2015 Mw 7.2 Sarez Earthquake plays a triggering role in the occurrence of the 2023 Tajikistan earthquake. Earthquake hazard on Sarez–Karakul Fault System and Sarez–Murghab Thrust System is enhanced due to the Coulomb stress loaded by the Tajikistan earthquake.
An Insight into the Warping Spatial Sampling Method in Subsurface Radar Imaging and Its Experimental Validation
Authors: Maisto Maria Antonia , Bhat Chandan , Solimene Raffaele
Published: June 2023

In this paper, we are concerned with microwave subsurface imaging achieved by inverting the linearized scattering operator arising from the Born approximation. In particular, we consider the important question of reducing the required data to achieve imaging. This can help to reduce the radar system’s cost and complexity and mitigate the imaging algorithm’s computational burden and the needed storage resources. To cope with these issues, in the framework of a multi-monostatic/multi-frequency configuration, we introduce a new spatial sampling scheme, named the warping method, that allows for a significant reduction in spatial measurements compared to other literature approaches. The basic idea is to introduce some variable transformations that “warp” the measurement space so that the reconstruction point-spread function obtained by adjoint inversion is recast as a Fourier-like transformation, which provides insights into how to achieve the sampling. In our previous contributions, we focused on presenting and checking the theoretical background with simple numerical examples. In this contribution, we briefly review the key components of the warping method and present its experimental validation by considering a realistic subsurface scattering scenario for the case of a buried water pipe. Essentially, we show that the latter succeeds in reducing the number of data compared to other approaches in the literature, without significantly affecting the reconstruction results.
Stereoscopic Monitoring Methods for Flood Disasters Based on ICESat-2 and Sentinel-2 Data
Authors: Cao Yongqiang , Wang Mengran , Yao Jiaqi , Mo Fan , Zhu Hong , Hu Liuru , Zhai Haoran
Published: June 2023

Climate change has led to an increased frequency of extreme precipitation events, resulting in increased damage from rainstorms and floods. Rapid and efficient flood forecasting is crucial. However, traditional hydrological simulation methods that rely on site distribution are limited by the limited availability of data and cannot provide fast and accurate flood monitoring information. Therefore, this study took the flood event in Huoqiu County in 2020 as an example and proposes a three-dimensional flood monitoring method based on active and passive satellites, which provides effective information support for disaster prevention and mitigation. The experimental results indicated the following: (1) the flood-inundated area was 704.1 km2, with the Jiangtang Lake section of the Huaihe River and the southern part of Chengdong Lake being the largest affected areas; (2) water levels in the study area ranged from 15.36 m to 17.11 m, which is 4–6 m higher than the original water level. The highest flood water level areas were the Jiangtang Lake section and the flat area in the south of Chengdong Lake, with Chengdong Lake and the north of Chengxi Lake having the greatest water level increase; (3) the flood water depth was primarily between 4 m and 7 m, with a total flood storage capacity of 2833.47 million m3, with Jiangtang Lake having the largest flood storage capacity; and (4) the rainstorm and flood disaster caused a direct economic loss of approximately CNY 7.5 billion and affected a population of approximately 91 thousand people. Three-dimensional monitoring of floods comprehensively reflects the inundation status of floods and can provide valuable information for flood prediction and management.
Correction: Riaz et al. Traffic Anomaly Prediction System Using Predictive Network. Remote Sens. 2022, 14, 447
Authors: Riaz Waqar , Gao Chenqiang , Azeem Abdullah , Saifullah  , Bux Jamshaid Allah , Ullah Asif
Published: June 2023

Since the article “Traffic Anomaly Prediction System Using Predictive Network” by Riaz et al. [...]
Unification of a Global Height System at the Centimeter-Level Using Precise Clock Frequency Signal Links
Authors: Shen Ziyu , Shen Wenbin , Zhang Shuangxi , Shum C. K. , Zhang Tengxu , He Lin , Cai Zhan , Xiong Si , Wang Lingxuan
Published: June 2023

The International Association of Geodesy (IAG) aims to establish the International Height Reference System (IHRS) as one of its primary scientific objectives. Central to the realization of the IHRS is global vertical datum unification, which requires the connection of existing local vertical height reference systems (VHS) robustly and consistently. However, conventional methods are not suitable for estimating the offsets between two distant local height systems. In this paper, we propose a framework for connecting two local VHSs using ultraprecise clock frequency signal links between satellites and ground stations, referred to as the satellite frequency signal transmission (SFST) approach. The SFST approach allows for the direct determination of the geopotential and height differences between two ground datum stations without any location restrictions between the two VHSs. The simulation results show that the VHSs of China and the US can be unified with an accuracy of several centimeters, provided that the stability of atomic clocks used on-board the satellite and at on-ground datum locations reaches 4.8×10−17τ−1/2 for an averaging time τ (in seconds). We conclude that the SFST approach shows promise for achieving centimeter-level accuracy in unifying the global vertical height datum and represents a new paradigm for the realization of the IHRS.
Correction: Wang et al. ShuffleCloudNet: A Lightweight Composite Neural Network-Based Method for Cloud Computation in Remote-Sensing Images. Remote Sens. 2022, 14, 5258
Authors: Wang Gang , Lu Zhiying , Wang Ping
Published: June 2023

In the original publication [...]