bluuebunny/crossref_metadata_2025 huggingface dataset:
Morphological, Molecular, and Nutritional Characterisation of the Globe Artichoke Landrace “Carciofo Ortano”
Authors: Alicandri Enrica , Paolacci Anna Rita , Catarcione Giulio , Del Lungo Alberto , Iacoponi Valentina , Pati Francesco , Scarascia Mugnozza Giuseppe , Ciaffi Mario
Published: May 2023

The present study focused on the molecular, morphological, and nutritional characterisation of a globe artichoke landrace at risk of genetic erosion still cultivated in the municipality of Orte (Lazio Region, Central Italy) and therefore named “Carciofo Ortano”. Molecular analysis based on SSR and ISSR markers was carried out on 73 genotypes selected at random from 20 smallholdings located in the Orte countryside and 17 accessions of landraces/clones belonging to the main varietal types cultivated in Italy. The results confirmed that “Carciofo Ortano” belongs to the “Romanesco” varietal typology and revealed the presence within the landrace of two distinct genetic populations named Orte 1 and Orte 2. Despite the high level of within-population genetic variation detected, the two populations were genetically differentiated from each other and from the landraces/clones of the main varietal types cultivated in Italy. Morphological and nutritional characterisation was performed on representative genotypes for each of the two populations of the “Carciofo Ortano” and the four landraces/clones included in the varietal platform of the PGI “CARCIOFO ROMANESCO DEL LAZIO” used as reference genotypes (“Campagnano”, “Castellammare”, “C3”, and “Grato 1”). Principal component analysis showed that, of the 43 morphological descriptors considered, 12, including plant height, head shape index, head yield, and earliness, allowed a clear grouping of genotypes, distinguishing Orte 1 and Orte 2 populations from the reference genotypes. Regarding the nutritional composition of heads, particular attention should be devoted to the Orte 2 genotypes for their high dietary fibre, inulin, flavonoid, and phenol content, a feature that could be highly appreciated by the market.
Genome-Wide Development of Polymorphic Microsatellite Markers and Genetic Diversity Analysis for the Halophyte Suaeda aralocaspica (Amaranthaceae)
Authors: Xu Wei , Wang Jiancheng , Tian Changyan , Shi Wei , Wang Lei
Published: May 2023

Suaeda aralocaspica, which is an annual halophyte, grows in saline deserts in Central Asia with potential use in saline soil reclamation and salt tolerance breeding. Studying its genetic diversity is critical for effective conservation and breeding programs. In this study, we aimed to develop a set of polymorphic microsatellite markers to analyze the genetic diversity of S. aralocaspica. We identified 177,805 SSRs from the S. aralocaspica genome, with an average length of 19.49 bp, which were present at a density of 393.37 SSR/Mb. Trinucleotide repeats dominated (75.74%) different types of motifs, and the main motif was CAA/TTG (44.25%). We successfully developed 38 SSR markers that exhibited substantial polymorphism, displaying an average of 6.18 alleles with accompanying average polymorphism information content (PIC) value of 0.516. The markers were used to evaluate the genetic diversity of 52 individuals collected from three populations of S. aralocaspica in Xinjiang, China. The results showed that the genetic diversity was moderate to high, with a mean expected heterozygosity (He) of 0.614, a mean Shannon’s information index (I) of 1.23, and a mean genetic differentiation index (Fst) of 0.263. The SSR markers developed in this study provide a valuable resource for future genetic studies and breeding programs of S. aralocaspica, and even other species in Suaeda.
Periquiteira (Cochlospermum orinocense): A Promising Amazon Fiber for Application in Composite Materials
Authors: Pinheiro Miriane Alexandrino , Ribeiro Maurício Maia , Rosa Diemison Lira Santa , Nascimento Damares da Cruz Barbosa , da Silva Alisson Clay Rios , dos Reis Marcos Allan Leite , Monteiro Sergio Neves , Candido Verônica Scarpini
Published: May 2023

Natural lignocellulosic fibers (NLFs) have in recent decades appeared as sustainable reinforcement alternatives to replace synthetic fibers in polymer composite material applications. In this work, for the first time, the periquiteira (Cochlospermum orinocense), a lesser known NLF from the Amazon region, was analyzed for its density and, by X-ray diffraction (XRD), to calculate the crystallinity index as well as the microfibrillar angle (MFA), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), scanning electron analysis (SEM) and tensile strength. The apparent density found for the periquiteira fiber was 0.43 g/cm3, one of the NLF’s lowest. XRD analysis indicated a crystallinity index of 70.49% and MFA of 7.32°. The TGA disclosed thermal stability up to 250 °C. The FTIR analysis indicated the presence of functional groups characteristic of NLFs. The SEM morphological analysis revealed that the periquiteira fiber presents fine bundles of fibrils and a rough surface throughout its entire length. The average strength value of the periquiteira fiber was found as 178 MPa. These preliminary results indicate that the periquiteira fiber has the potential to be used as a reinforcing agent in polymeric matrices and can generate a lightweight composite with excellent mechanical properties that can be used in various industrial sectors.
Scaffolds and Surfaces with Biomedical Applications
Authors: Serafim Andrada , Voicu Stefan Ioan
Published: May 2023

The engineering of scaffolds and surfaces with enhanced properties for biomedical applications represents an ever-expanding field of research that is continuously gaining momentum [...]
Synthesis and Characterization of Novel Wholly Aromatic Copolyesters Based on 4′-Hydroxybiphenyl-3-Carboxylic and 3-Hydroxybenzoic Acids
Authors: Mikhailov Pavel A. , Zuev Kirill V. , Kulichikhin Valery G.
Published: May 2023

A series of new wholly aromatic (co)polyesters based on m-substituted bifunctional comonomers—4′-hydroxybiphenyl-3-carboxylic (3HBCA) and 3-hydroxybenzoic (3HBA) acids with molar ratios of 3HBCA:3HBA from 0:100 to 60:40, respectively—was synthesized. NMR and FTIR spectroscopy methods proved the full compliance of the copolymer composition with the target ratio of comonomers, as well as high compositional homogeneity (absence of block sequences). The resulting copolyesters have a sufficiently high molecular weight and their intrinsic viscosity values are in the range of 0.6–0.8 dL/g. Thermal analysis showed that all 3HBCA-3HBA copolyesters are amorphous, and with an increase in the content of biphenyl units (3HBCA), the glass transition temperature increases significantly (up to 190 °C). The onset of the intense thermal decomposition of the synthesized polyesters occurs above 450 °C. Thus, this indicates a sufficiently high thermal stability of these polyesters. Rheological measurements have shown that melts of copolyesters with a high content of 3HBCA units exhibit anisotropic properties. At the same time, the method of polarization optical microscopy did not confirm the transition to the liquid crystal state for these polyesters. These results confirm that it is possible to obtain high-performance polyesters based on 3HBCA, but not a mesogenic comonomer. Thus, 3HBCA is a promising comonomer for the synthesis of new thermotropic copolyesters with controlled anisotropic properties.
Physical Properties of Additively Manufactured Tooth-Colored Material Attached to Denture Base-Colored Material in a Printed Monolithic Unit
Authors: Mohamed Amr , Takaichi Atsushi , Kajima Yuka , Takahashi Hidekazu , Wakabayashi Noriyuki
Published: May 2023

Additive manufacturing is an emerging technology that has been successfully used in dentistry for denture fabrication. However, the conventional issue of tooth debonding exists in additively manufactured dentures. In this study, we investigated the physical properties of conventional teeth attached to a heat-cured denture base material compared to additively manufactured tooth-coloured materials attached to denture base-coloured materials in a printed monolithic unit. We designed a model consisting of a tooth attached to a cylindrical base to fabricate the additively manufactured group and the conventional group. All groups were tested for fracture load before and after thermocycling, water sorption, solubility, and shape accuracy. The Mann–Whitney U test was used for statistical analysis. The fracture load of the additively manufactured group was significantly higher than that of the conventional group after thermocycling (p = 0.019). The water sorption of the conventional group was significantly lower than that of the additively manufactured group (p = 0.000), whereas there was no significant difference in the water solubility between them (p = 0.192). The shape accuracy of the additively manufactured group was significantly better than that of the conventional group (p < 0.05). In conclusion, additive monolithic manufacturing technology may provide an alternative way to enhance the fracture load between the teeth and denture bases.
A Light/Pressure Bifunctional Electronic Skin Based on a Bilayer Structure of PEDOT:PSS-Coated Cellulose Paper/CsPbBr3 QDs Film
Authors: Li Wenhao , Jia Jingyu , Sun Xiaochen , Hao Sue , Ye Tengling
Published: May 2023

With the continuous development of electronic skin (e-skin), multifunctional e-skin is approaching, and in some cases even surpassing, the capabilities of real human skin, which has garnered increasing attention. Especially, if e-skin processes eye’s function, it will endow e-skins more powerful advantages, such as the vision reparation, enhanced security, improved adaptability and enhanced interactivity. Here, we first study the photodetector based on CsPbBr3 quantum dots film and the pressure sensor based on PEDOT: PSS-coated cellulose paper, respectively. On the base of these two kinds of sensors, a light/pressure bifunctional sensor was successfully fabricated. Finally, flexible bifunctional sensors were obtained by using a flexible interdigital electrode. They can simultaneously detect light and pressure stimulation. As e-skin, a high photosensitivity with a switching ratio of 168 under 405 nm light at a power of 40 mW/cm2 was obtained and they can also monitor human motions in the meantime. Our work showed that the strategy to introduce perovskite photodetectors into e-skins is feasible and may open a new way for the development of flexible multi-functional e-skin.
Seawater Effects on Thermally Aged Ambient Cured Carbon/Epoxy Composites: Moisture Kinetics and Uptake Characteristics
Authors: Karbhari Vistasp M. , Acharya Rabina , Hong SoonKook
Published: May 2023

Carbon fiber-reinforced epoxy matrix composites using ambient- and moderate-temperature curing non-autoclave processes have broad applicability in marine, offshore, and naval applications. This research focuses on the characterization of moisture kinetics of ambient cured carbon/epoxy composites subject to immersion in seawater for up to 72 weeks after prior periods of extended thermal aging. A two-stage model is shown to best describe the overall kinetics and response. The level of maximum moisture uptake shows an increasing trend with the temperature and time of prior thermal aging, reaching asymptotic levels at the highest levels. The transition point is seen to represent a shift between the diffusion and relaxation-/deterioration-based dominant regimes, and the ratio of uptake at the transition point to the maximum uptake can be correlated to the relaxation coefficient. Diffusivity, as expected, generally increases with the temperature of prior aging and shows changes based on the level of post-curing and network changes with time. Moisture uptake kinetics and characteristics developed through the sequence of exposures provide a better understanding of phenomena towards the development of a future comprehensive model capable of long-term prediction based on the sequential prior history of exposure to elevated temperatures and immersion in seawater.
Study and Microanalysis on the Effect of the Addition of Polypropylene Fibres on the Bending Strength and Carbonization Resistance of Manufactured Sand Concrete
Authors: Tan Yan , Ma Chong , Zhao Ben , Xiong Wei , Chen Xingxiang , Yu Jiangtao
Published: May 2023

To popularize the complete replacement of natural sand with manufactured sand, a study was performed to determine the effect of adding polypropylene fibres (PPFs) to increase the bending strength and carbonization resistance of manufactured sand concrete (MSC). A 2 × 3 factorial design with the content and length of PPF as variables was used to establish a carbonization depth prediction model and a response surface model (RSM). The phase composition and microstructure of polypropylene-fibre-reinforced manufactured sand concrete (PPF-MSC) were analysed using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results show the addition of PPF with different contents and lengths increases the bending strength of PPF-MSC to varying degrees, while reducing the carbonization depth and increasing the dynamic elastic modulus after 28 days of carbonization. The highest bending strength (6.12 MPa) and carbonization resistance of PPF-MSC are obtained by the addition of 1 kg/m3 of 12 mm PPF, while the carbonization depth and an increase in the dynamic elastic modulus after 28 days of carbonization are maintained at a minimum of 2.26% and 1.94 mm, respectively. A prediction model was established to obtain a formula for the PPF-MSC carbonization depth in terms of the content and length of PPF and the carbonization time. The following results were obtained from the RSM: compared to the PPF length, the PPF content has a larger impact on the PPF-MSC bending strength and a smaller impact on the PPF-MSC carbonization resistance; there is no significant interaction between the content and length of PPF; and the predicted and measured values are close, indicating that the model is highly reliable. A comparison of the XRD patterns and SEM micrographs of PPF-MSC and MSC after 28 days of carbonization show a lower peak intensity of CaCO3 in the pattern for the carbonized area for PPF-MSC than for MSC and considerably fewer surface pores and cracks in PPF-MSC than in MSC. These results indicate that the addition of PPF increases the compactness of MSC and creates an effective resistance to the erosion by water molecules and carbon dioxide (CO2), thus enhancing the bending strength and carbonization resistance of MSC.
Utilization of Prepared Nanocellulose as a Biopolymer for Adsorption Kinetics of Cobalt Ions from Wastewater
Authors: Bin Bandar Khaled , Aljlil Saad
Published: May 2023

This study evaluated nanocellulose derived from discarded palm leaves for its ability to remove cobalt ions from industrial wastewater. The process involved extracting cellulose nanocrystals (CNCs) from date palm leaves through a series of repeated chemical treatments. The study examined the adsorption rates of cobalt ions under various conditions using different techniques. Two equilibrium models, the Langmuir and Freundlich models, were employed, and the Langmuir model was found to be consistent with the experimental data. The maximum amount of cobalt ions adsorbed at room temperature was 5.98 mg/g. Furthermore, several kinetic models were used to gain insight into the adsorption mechanism, including the pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models. The pseudo-second-order model provided an accurate description of the adsorption process, while the Elovich equation suggested a chemical reaction between cobalt ions and nanocellulose, involving multiple chemical reactions and mass-transfer processes. Kinetic parameters were critical in interpreting the results, and the study’s findings were in agreement with the pseudo-second-order and intraparticle models, indicating general chemical reactions and diffusion resistance.
Recent Advancements of Polymeric Membranes in Anion Exchange Membrane Water Electrolyzer (AEMWE): A Critical Review
Authors: Vinodh Rajangam , Kalanur Shankara Sharanappa , Natarajan Sadesh Kumar , Pollet Bruno G.
Published: May 2023

Water electrolysis coupled with renewable energy is one of the principal methods for producing green hydrogen (or renewable hydrogen). Among the different electrolysis technologies, the evolving anion exchange membrane water electrolysis (AEMWE) shows the utmost promise for the manufacture of green hydrogen in an inexpensive way. In the present review, we highlight the most current and noteworthy achievements of AEMWE, which include the advancements in increasing the polymer anionic conductivity, understanding the mechanism of degradation of AEM, and the design of the electrocatalyst. The important issues affecting the AEMWE behaviour are highlighted, and future constraints and openings are also discussed. Furthermore, this review provides strategies for producing dynamic and robust AEMWE electrocatalysts.
Green Synthesis and Characteristics of Cellulose Nanocrystal/Poly Acrylic Acid Nanocomposite Thin Film for Organic Dye Adsorption during Water Treatment
Authors: Almuslem Amani Saleh , Alnaim Nisrin , Ibrahim Sobhy S. , Ibrahim Mostafa A.
Published: May 2023

Nanocellulose shows potential as an effective natural adsorbent for removing harmful contaminants from wastewater. This paper describes the development of innovative nanocellulose thin films made of cellulose nanocrystals (CNCs), polyacrylic acid (PAA), and active carbon (AC) as adsorbent materials for absorbing azo dyes from wastewater. The CNCs were recovered from sugarcane bagasse using alkali treatment and acid hydrolysis. The composition and processing parameters of the thin films were optimized, and their adsorption capacity was determined using thermodynamic isotherms and adsorption kinetics. Adsorption characteristics such as the methylene blue (MB) dye concentration, contact time, temperature, and pH were investigated to determine how they affected adsorption. The results show that the adsorption process follows pseudo-second-order kinetics. At an adsorbent mass of 50 mg, dye concentration of 50 ppm in 50 mL, and contact period of 120 min at 25 °C, the thin film comprising 64 wt% CNC, 16 wt% PAA, and 20 wt% AC showed high dye removal efficiency (86.3%) and adsorption capacity (43.15 mg/g). The MB removal efficiency increased to 95.56% and the adsorption capacity to 47.78 mg/g when the medium’s pH was gradually increased from neutral to alkaline. The nontoxicity, low production cost, water stability, easy recovery, and high adsorption capacity of these membranes make them suitable for water treatment systems.
Effect of Chain Structure on the Various Properties of the Copolymers of Fluorinated Norbornenes with Cyclooctene
Authors: Adzhieva Olga A. , Gringolts Maria L. , Denisova Yulia I. , Shandryuk Georgiy A. , Litmanovich Ekaterina A. , Nikiforov Roman Yu. , Belov Nikolay A. , Kudryavtsev Yaroslav V.
Published: May 2023

Fluorinated polymers are attractive due to their special thermal, surface, gas separation, and other properties. In this study, new diblock, multiblock, and random copolymers of cyclooctene with two fluorinated norbornenes, 5-perfluorobutyl-2-norbornene and N-pentafluorophenyl-exo-endo-norbornene-5,6-dicarboximide, are synthesized by ring-opening metathesis copolymerization and macromolecular cross-metathesis in the presence of the first- to third-generation Grubbs’ Ru-catalysts. Their thermal, surface, bulk, and solution characteristics are investigated and compared using differential scanning calorimetry, water contact angle measurements, gas permeation, and light scattering, respectively. It is demonstrated that they are correlated with the chain structure of the copolymers. The properties of multiblock copolymers are generally closer to those of diblock copolymers than of random ones, which can be explained by the presence of long blocks capable of self-organization. In particular, diblock and multiblock fluorine-imide-containing copolymers show a tendency to form micelles in chloroform solutions well below the overlap concentration. The results obtained may be of interest to a wide range of researchers involved in the design of functional copolymers.
Rheological and Aging Properties of Vegetable Oil-Based Polyurethane (V-PU) Modified Asphalt
Authors: Xia Lei , Cao Dongwei , Zhang Hongliang
Published: May 2023

To study the rheological and aging properties of vegetable oil–based polyurethane (V-PU) modified asphalt, V-PU terminated with an –NCO group was synthesized from renewable castor oil, and liquefied MDI-100LL and 10–40 wt% V-PU modified asphalts were prepared. Temperature classification, multiple stress creep recovery (MSCR), and linear amplitude scanning (LAS) tests were carried out. The results showed that the modulus, the creep recovery rate (R), and the yield stress and yield strain of the V-PU modified asphalts significantly increased in the order: 0 wt% < 10 wt% < 20 wt% < 40 wt% < 30 wt%, while the phase angle and the unrecoverable creep compliance (Jnr) changed in the opposite order, and the high temperature grade of 30 wt% V-PU modified asphalt was 4 grades higher than that of the base asphalt, which indicated that the addition of V-PU enhanced the fatigue, permanent deformation, and recovery deformation resistance. The 30 wt% sample exhibited phase inversion had the best performance. Comprehensive FTIR, GPC, and fluorescence microscopy analyses showed that the molecular weight significantly increased and the V-PU molecules agglomerated after aging. The excess –NCO groups of V-PU prepolymer react with water in the air and the active hydrogen in the asphalt system and finally form a cross-linked three-dimensional network structure with the asphalt to improve performance. The mechanism of intramolecular cementation reaction and the aging process of V-PU modified asphalt was creatively derived.
Buried River Valleys of the Neogene and Early Quaternary in the Middle Volga Region, European Russia
Authors: Petrova Elena V. , Gusarov Artyom V. , Beylich Achim A.
Published: May 2023

Buried river valleys from the Neogene–Quaternary time are widespread throughout the Middle Volga region of the Russian Plain. They have been studied for a long period, since the 1940s, with the last major generalizations dating back to the 1980s. This paper presents new results based on GIS mapping using materials from the state geological study of the region in 1960–1970, 1984–1996 and 2000–2002. On the whole, the pattern of the buried valley network is close to the modern valley network of the region. During the Quaternary, the right-sided displacement of the valley incisions prevailed. The incisions of modern river valleys are located above the Neogene (pre-Akchagyl) incisions almost throughout the entire territory. The vertical displacement amplitude ranges from 30 to 200 m. The morphometric characteristics of the paleovalleys (the depth and width of the incisions, as well as the gradients of the bottoms of the paleovalleys) exceeded modern ones. The maximum values were typical for the middle Paleo-Volga valley: the width of the valley reached 10 km, the incision depth was−201.4 m below sea level and the bottom gradient was 0.9–5.0 m/km. The most important factor that influenced the position of paleovalleys and their morphological appearance was fluctuations in the level of the Caspian paleowaterbody. According to this study, the development of paleovalleys began in the Miocene and ended in the Early Quaternary. The alluvial–lacustrine type of sedimentation was predominant. The results of this work contribute to the study of the paleogeography of the Cenozoic of the southeast of the Russian Plain.
Municipal Waste Recycling Customer Education and Communication in Slovenia and Croatia
Authors: Aver Boštjan , Alfirević Nikša , Fošner Ajda
Published: May 2023

The aim of this paper is twofold: (a) to present the existing regional research related to customer education and communication in municipal waste recycling from the viewpoint of a comparative bibliometric analysis and (b) to illustrate how municipal waste recycling practices in the two countries mirror the theoretical trends identified in the literature and the EU institutional and policy requirements. We discuss the practical implementation of municipal waste recycling practices in the two European countries and provide practical recommendations for local governments, municipal companies, and other stakeholders of the municipal waste management process.
Microfactory Design for Valorization of E-Waste Plastics (Acrylonitrile-Butadiene-Styrene, Polycarbonate, and Polypropylene) on Additive Manufacturing Sector
Authors: Moure Abelenda Alejandro , Aiouache Farid
Published: May 2023

Less than half of e-waste plastics are sorted worldwide, and this rate is likely to decline as major processing countries have banned importation of e-waste plastics. This forces the development of decentralized processing facilities, also known as microfactories. The present work investigates the recyclability of different grades of acrylonitrile-butadiene-styrene (ABS) copolymer, polycarbonate, and polypropylene, which were found to be very abundant in a recycling site in the UK. The determination of the matrix relied on the resin identification codes imprinted in the e-waste plastics and subsequent Fourier-transform infrared spectroscopy (FTIR). Melt-blend extrusion technology enabled the valorization of the wasted thermoplastics as 3D filament without significant degradation of the polymers. The recycled materials maintained the tensile strength at around 2.5 MPa in agreement with the specifications offered by virgin polymers. Further characterization was done by means of laser microscope, thermogravimetric analysis, and X-ray fluorescence to determine the commercial viability of the recycled filament. A modified solvent-based method was developed with acetone to remove the brominated flame retardants: 25 g/100 mL, 30 min of contact time, and 4 extraction steps. The FTIR results show that the degradation of the rubbery dispersed phase corresponding to the butadiene can be accumulated in the less soluble fraction of the extracted ABS.
Jethro and Moses in Dialogue (Exodus 18: 8–26): Ethics of Communitarian Responsibility
Authors: Sciberras Paul
Published: May 2023

Jethro’s dialogue with his son-in-law, Moses, in the Book of Exodus 18: 8–26 can be summarised according to the four-fold elements of subsidiarity, communitarian responsibility, delegation, and synodality, which lead to focus in life. The Elder priest of Midian, in north-western Arabia, advises his son-in-law to practise subsidiarity and communitarian ethical responsibility by undertaking the fundamental task of teaching the precepts, statutes, and instructions that would form the backbone of the twelve-tribe nation of Israel. Subsidiarity and delegation were to be exercised by different levels of leadership, together with Moses himself, in the choice of the exemplary leaders who would both teach Israel and judge minor issues among its people. Finally, synodality is advised by Jethro so that the People of Israel and their leaders can reach their ultimate aim in the Promised Land in peace. Subsidiarity, communitarian responsibility, delegation and synodality would bring Israel as a nation gathered around their one God, YHWH, according to the aim for which they were called from slavery in Egypt to freedom in Canaan.
Tradition and Transmission: Rocana Assembly in Niche no. 5 at Feilai Feng and Huayan Teaching during the Song Period
Authors: Chang Qing
Published: May 2023

The Huayan sutras are important historical references for the Chinese worship of the Rocana Buddha; however, these Huayan sutras provide little help in understanding the worship for the larger Rocana triad (i.e., Rocana Buddha flanked by two bodhisattvas) in niche no. 5 at the Feilai Feng complex. The Rocana triad images are primarily linked to the Buddhist texts written by Chinese monks which established the principle for teaching the Huayan ritual during the Tang period. With regard to the iconographic characteristics of the two bodhisattvas of the triad in niche no. 5, the bodhisattva Samantabhadra rides an elephant, while the bodhisattva Manjusri rides a lion. They are associated with Buddhist texts and artistic productions beyond the Huayan school and are possibly related to esoteric Buddhism. Similarly, the crowned Rocana seen in niche no. 5 is likely derived from an older tradition dating to the Tang and Five Dynasties periods. Similar descriptions can be found in esoteric Buddhist texts and images. Nevertheless, niche no. 5 is the earliest extant example of such a Rocana triad, wherein the triad is represented by a central crowned Buddha with a special hand gesture or mudra, who is flanked by two bodhisattvas riding animals. From niche no. 5, one can see the development of the Huayan Rocana triad within the tenth century. The combination of elements seen in this niche also indicates that Buddhist artists were not limited by the boundaries of different schools or teachings when they created a new form of iconography. The specific iconography of niche no. 5 can be linked to the Han-style Buddhist artistic traditions from previous periods, such as the Tang, Five Dynasties/Wuyue Kingdom. Ultimately, the contemporary Northern Song capital, Kaifeng, was likely the most direct influence. The Rocana Buddhist triad at niche no. 5 is reflected in the iconography of the same triad installed at the Huiyin monastery at a later time during the Northern Song Dynasty. In turn, the similarities between the images in niche no. 5 and those from other regions, such as Sichuan, Yunnan, Korea and Japan, reveal the connection between the Huiyin monastery and these other sites.
Long-Term Change of Coastline Length along Selected Coastal Countries of Eurasia and African Continents
Authors: Yang Fan , Zhang Li , Chen Bowei , Li Kaixin , Liao Jingjuan , Mahmood Riffat , Hasan Mohammad Emran , Mamun M. M. Abdullah Al , Raza Syed Ahmed , Sutrisno Dewayany
Published: May 2023

The acquisition of dynamic coastline change at fine spatial and temporal resolution is essential for enhancing sustainable coastal economic development and coastal environmental conservation. Port construction, land reclamation, urban development, and sediment deposition have resulted in extensive coastline change. In this study, the coastlines along the 56 coastal countries in 1990, 2000, 2010, 2015, and 2020 were delineated and classified into six categories using Landsat time–series images. Five relevant indices, i.e., the length, length ratio, length change rate, index of coastline utilization degree (ICUD), and fractal dimension (FD), were calculated to analyze and explore the spatiotemporal pattern of the coastlines. The results indicate that: (1) The overall length of the coastlines has increased from 3.45 × 105 km to 3.48 × 105 km in the past 30 years, with a net increase of nearly 3904 km. Between 1990 and 2020, the length of the artificial coastline increased by about 13,835 km (4.9~8.8%), while the length of the natural coastline decreased by 9932 km (95.1~91.2%). The increase in artificial coastline is concentrated in Southeast Asia and South Asia. (2) The coastline fractal dimensions (FDs) of countries and continents show that the average FD values of countries in South Asia (1.3~1.4) and Southeast Asia (1.2~1.3) were higher than other countries in the study regions, meaning that the coastlines in South Asia and Southeast Asia are more complex and curved. (3) The value of the ICUD index increased consistently between 1990 and 2015 (177.7~186.6) but decreased sharply between 2015 and 2020 (186.6~162.4), implying that the impact of human activities on the coastline continued to increase until 2015 and began to decrease after 2015. Our study examined the changes in various types of coastlines, which could be significant for sustainable development and environmental protection in coastal areas.
A Novel Point Target Attitude Compensation Method Using Electromagnetic Reflectance Theory
Authors: Han Yonghui , Lu Pingping , Hou Wentao , Gao Yao , Wang Robert
Published: May 2023

During the process of the airborne synthetic aperture radar (SAR) system platform in space, platform attitude deflection is inevitable. However, large attitude deflection angles are unacceptable for polarimetric calibration using point targets, especially the dihedral, which is very sensitive to the pointing angle of the radar. To mitigate the impact of attitude angles on calibration accuracy, attitude compensation of the corner reflector is necessary during the calibration process. The conventional approach to attitude compensation typically maps the three-dimensional attitude angle information to the one-dimensional polarimetric orientation angle (POA) information. However, the reduction of dimension inevitably results in information loss, leading to errors that affect calibration performance when the attitude angle is large. In order to ensure the accuracy of point target calibration, this paper proposes a novel point target compensation method based on the reflection theory of electromagnetic waves. This method is based on three-dimensional attitude angle information and has higher reliability than the POA method. Finally, this paper calculates the distance between the scattering matrices obtained after compensation based on the proposed method and the POA method to obtain the difference in the performance of the two methods. Through a simulation, this paper finds that when the attitude angle is small, the results of the two schemes are approximately the same, but as the attitude angle increases, the error between the two gradually increases. This suggests that the proposed method has greater advantages in the case of attitude deflection. Furthermore, the proposed method does not require additional information supplementation compared with the equivalent POA method, making it highly practical.
TESR: Two-Stage Approach for Enhancement and Super-Resolution of Remote Sensing Images
Authors: Ali Anas M. , Benjdira Bilel , Koubaa Anis , Boulila Wadii , El-Shafai Walid
Published: May 2023

Remote Sensing (RS) images are usually captured at resolutions lower than those required. Deep Learning (DL)-based super-resolution (SR) architectures are typically used to increase the resolution artificially. In this study, we designed a new architecture called TESR (Two-stage approach for Enhancement and super-resolution), leveraging the power of Vision Transformers (ViT) and the Diffusion Model (DM) to increase the resolution of RS images artificially. The first stage is the ViT-based model, which serves to increase resolution. The second stage is an iterative DM pre-trained on a larger dataset, which serves to increase image quality. Every stage is trained separately on the given task using a separate dataset. The self-attention mechanism of the ViT helps the first stage generate global and contextual details. The iterative Diffusion Model helps the second stage enhance the image’s quality and generate consistent and harmonic fine details. We found that TESR outperforms state-of-the-art architectures on super-resolution of remote sensing images on the UCMerced benchmark dataset. Considering the PSNR/SSIM metrics, TESR improves SR image quality as compared to state-of-the-art techniques from 34.03/0.9301 to 35.367/0.9449 in the scale ×2. On a scale of ×3, it improves from 29.92/0.8408 to 32.311/0.91143. On a scale of ×4, it improves from 27.77/0.7630 to 31.951/0.90456. We also found that the Charbonnier loss outperformed other loss functions in the training of both stages of TESR. The improvement was by a margin of 21.5%/14.3%, in the PSNR/SSIM, respectively. The source code of TESR is open to the community.
Benchmark for Building Segmentation on Up-Scaled Sentinel-2 Imagery
Authors: Illarionova Svetlana , Shadrin Dmitrii , Shukhratov Islomjon , Evteeva Ksenia , Popandopulo Georgii , Sotiriadi Nazar , Oseledets Ivan , Burnaev Evgeny
Published: May 2023

Currently, we can solve a wide range of tasks using computer vision algorithms, which reduce manual labor and enable rapid analysis of the environment. The remote sensing domain provides vast amounts of satellite data, but it also poses challenges associated with processing this data. Baseline solutions with intermediate results are available for various tasks, such as forest species classification, infrastructure recognition, and emergency situation analysis using satellite data. Despite these advances, two major issues with high-performing artificial intelligence algorithms remain in the current decade. The first issue relates to the availability of data. To train a robust algorithm, a reasonable amount of well-annotated training data is required. The second issue is the availability of satellite data, which is another concern. Even though there are a number of data providers, high-resolution and up-to-date imagery is extremely expensive. This paper aims to address these challenges by proposing an effective pipeline for building segmentation that utilizes freely available Sentinel-2 data with 10 m spatial resolution. The approach we use combines a super-resolution (SR) component with a semantic segmentation component. As a result, we simultaneously consider and analyze SR and building segmentation tasks to improve the quality of the infrastructure analysis through medium-resolution satellite data. Additionally, we collected and made available a unique dataset for the Russian Federation covering area of 1091.2 square kilometers. The dataset provides Sentinel-2 imagery adjusted to the spatial resolution of 2.5 m and is accompanied by semantic segmentation masks. The building footprints were created using OpenStreetMap data that was manually checked and verified. Several experiments were conducted for the SR task, using advanced image SR methods such as the diffusion-based SR3 model, RCAN, SRGAN, and MCGR. The MCGR network produced the best result, with a PSNR of 27.54 and SSIM of 0.79. The obtained SR images were then used to tackle the building segmentation task with different neural network models, including DeepLabV3 with different encoders, SWIN, and Twins transformers. The SWIN transformer achieved the best results, with an F1-score of 79.60.
Precipitation Characteristics across the Three River Headwaters Region of the Tibetan Plateau: A Comparison between Multiple Datasets
Authors: Du Juan , Yu Xiaojing , Zhou Li , Ren Yufeng , Ao Tianqi
Published: May 2023

Precipitation is crucial for managing water resources in the Three River Headwaters (TRH) region of the Tibetan Plateau (TP). Gridded precipitation datasets across the TRH region exhibit significant discrepancies in their results. Previous studies have primarily focused on assessing average or extreme precipitation for a single dataset or several datasets. In this study, based on the observed gridded precipitation dataset (CN05.1), a comprehensive evaluation of the climatic features and extreme precipitation across the TRH region from 1983 to 2014 is performed by employing two gauge-based gridded datasets (GPCC and CRU), two satellite-derived precipitation datasets (P-CDR and IMERG), and two reanalysis precipitation datasets (ERA5 and CRA40). The results show that all datasets are consistent in reproducing the climatology, interannual variability, and annual cycle of precipitation in the TRH region. However, the different datasets exhibit significant discrepancies in characterizing the long-term trends and extreme precipitation events. P-CDR and GPCC provide a good representation of the spatial variability of the annual mean climatology. ERA5 and CRU are more reliable in capturing interannual variabilities. The long-term trends can be closely described by employing CRU. P-CDR and GPCC exhibit higher skills in terms of the annual cycle. P-CDR performs better than IMERG for daily precipitation in terms of probability distributions and other assessment metrics. P-CDR and IMERG have advantages and disadvantages in characterizing the nine extreme precipitation indices. This study demonstrates a comprehensive comparison method using multiple precipitation datasets to gain essential insight into the strengths and weaknesses of various datasets across the TRH region.
Spatial Multi-Criteria Analysis of Water-Covered Areas: District City of Katowice—Case Study
Authors: Janczewska Natalia , Matysik Magdalena , Absalon Damian , Pieron Łukasz
Published: May 2023

The following databases contains information on land use with water in Poland: Corine Land Cover (CLC), the Urban Atlas (UA); Database of Topographic Objects (BDOT) the digital Map of Poland’s Hydrographic Division (MPHP); and the Register of Lands and Buildings (EGiB). All these data are referenced in scientific analyses and the Polish water management system, so the results of their processing should be the same (or at least similar); if not, output materials will be inconsistent and unreliable. In the Katowice sample, we checked the quality of this data using multi-criteria analyses, which is based on a grid of equal-area hexagons. Additionally, we applied the Normalized Difference Water Index to check real-time water presence. We detected discrepancies between all the data. The CLC does not reference any flowing water in Katowice. Most data overlapped between MPHP and BDOT, and both databases were similar to UA. However, a lot of uncertainty was also observed in the EGiB, which is considered to be the most accurate of the databases surveyed. In conclusion, we argue that water land cover data should be used with caution, and depending on the scales of analysis, that most actual data could be remote sensed data. We also include a diagram which can be useful in the data selection process.
Meta-Knowledge Guided Weakly Supervised Instance Segmentation for Optical and SAR Image Interpretation
Authors: Chen Man , Zhang Yao , Chen Enping , Hu Yahao , Xie Yifei , Pan Zhisong
Published: May 2023

The interpretation of optical and synthetic aperture radar (SAR) images in remote sensing is general for many tasks, such as environmental monitoring, marine management, and resource planning. Instance segmentation of optical and SAR images, which can simultaneously provide instance-level localization and pixel-level classification of objects of interest, is a crucial and challenging task in image interpretation. Considering that most current methods for instance segmentation of optical and SAR images rely on expensive pixel-level annotation, we develop a weakly supervised instance segmentation (WSIS) method to balance the visual processing requirements with the annotation cost. First, we decompose the prior knowledge of the mask-aware task in WSIS into three meta-knowledge components: fundamental knowledge, apparent knowledge, and detailed knowledge inspired by human visual perception habits of “whole to part” and “coarse to detailed.” Then, a meta-knowledge-guided weakly supervised instance segmentation network (MGWI-Net) is proposed. In this network, the weakly supervised mask (WSM) head can instantiate both fundamental knowledge and apparent knowledge to perform mask awareness without any annotations at the pixel level. The network also includes a mask information awareness assist (MIAA) head, which can implicitly guide the network to learn detailed information about edges through the boundary-sensitive feature of the fully connected conditional random field (CRF), facilitating the instantiation of detailed knowledge. The experimental results show that the MGWI-Net can efficiently generate instance masks for optical and SAR images and achieve the approximate instance segmentation results of the fully supervised method with about one-eighth of the annotation production time. The model parameters and processing speed of our network are also competitive. This study can provide inexpensive and convenient technical support for applying and promoting instance segmentation methods for optical and SAR images.
Evaluation of River Water Quality Index Using Remote Sensing and Artificial Intelligence Models
Authors: Najafzadeh Mohammad , Basirian Sajad
Published: May 2023

To restrict the entry of polluting components into water bodies, particularly rivers, it is critical to undertake timely monitoring and make rapid choices. Traditional techniques of assessing water quality are typically costly and time-consuming. With the advent of remote sensing technologies and the availability of high-resolution satellite images in recent years, a significant opportunity for water quality monitoring has arisen. In this study, the water quality index (WQI) for the Hudson River has been estimated using Landsat 8 OLI-TIRS images and four Artificial Intelligence (AI) models, such as M5 Model Tree (MT), Multivariate Adaptive Regression Spline (MARS), Gene Expression Programming (GEP), and Evolutionary Polynomial Regression (EPR). In this way, 13 water quality parameters (WQPs) (i.e., Turbidity, Sulfate, Sodium, Potassium, Hardness, Fluoride, Dissolved Oxygen, Chloride, Arsenic, Alkalinity, pH, Nitrate, and Magnesium) were measured between 14 March 2021 and 16 June 2021 at a site near Poughkeepsie, New York. First, Multiple Linear Regression (MLR) models were created between these WQPs parameters and the spectral indices of Landsat 8 OLI-TIRS images, and then, the most correlated spectral indices were selected as input variables of AI models. With reference to the measured values of WQPs, the WQI was determined according to the Canadian Council of Ministers of the Environment (CCME) guidelines. After that, AI models were developed through the training and testing stages, and then estimated values of WQI were compared to the actual values. The results of the AI models’ performance showed that the MARS model had the best performance among the other AI models for monitoring WQI. The results demonstrated the high effectiveness and power of estimating WQI utilizing a combination of satellite images and artificial intelligence models.
ACTNet: A Dual-Attention Adapter with a CNN-Transformer Network for the Semantic Segmentation of Remote Sensing Imagery
Authors: Zhang Zheng , Liu Fanchen , Liu Changan , Tian Qing , Qu Hongquan
Published: May 2023

In recent years, the application of semantic segmentation methods based on the remote sensing of images has become increasingly prevalent across a diverse range of domains, including but not limited to forest detection, water body detection, urban rail transportation planning, and building extraction. With the incorporation of the Transformer model into computer vision, the efficacy and accuracy of these algorithms have been significantly enhanced. Nevertheless, the Transformer model’s high computational complexity and dependence on a pre-training weight of large datasets leads to a slow convergence during the training for remote sensing segmentation tasks. Motivated by the success of the adapter module in the field of natural language processing, this paper presents a novel adapter module (ResAttn) for improving the model training speed for remote sensing segmentation. The ResAttn adopts a dual-attention structure in order to capture the interdependencies between sets of features, thereby improving its global modeling capabilities, and introduces a Swin Transformer-like down-sampling method to reduce information loss and retain the original architecture while reducing the resolution. In addition, the existing Transformer model is limited in its ability to capture local high-frequency information, which can lead to an inadequate extraction of edge and texture features. To address these issues, this paper proposes a Local Feature Extractor (LFE) module, which is based on a convolutional neural network (CNN), and incorporates multi-scale feature extraction and residual structure to effectively overcome this limitation. Further, a mask-based segmentation method is employed and a residual-enhanced deformable attention block (Deformer Block) is incorporated to improve the small target segmentation accuracy. Finally, a sufficient number of experiments were performed on the ISPRS Potsdam datasets. The experimental results demonstrate the superior performance of the model described in this paper.