bluuebunny/crossref_metadata_2025 huggingface dataset:
Capturing Genetic Diversity in Seed Collections: An Empirical Study of Two Congeners with Contrasting Mating Systems
Authors: Lu-Irving Patricia , Bragg Jason G. , Rossetto Maurizio , King Kit , O’Brien Mitchell , van der Merwe Marlien M.
Published: January 2023

Plant mating systems shape patterns of genetic diversity and impact the long-term success of populations. As such, they are relevant to the design of seed collections aiming to maximise genetic diversity (e.g., germplasm conservation, ecological restoration). However, for most species, little is known empirically about how variation in mating systems and genetic diversity is distributed. We investigated the relationship between genetic diversity and mating systems in two functionally similar, co-occurring species of Hakea (Proteaceae), and evaluated the extent to which genetic diversity was captured in seeds. We genotyped hundreds of seedlings and mother plants via DArTseq, and developed novel implementations of two approaches to inferring the mating system from SNP data. A striking contrast in patterns of genetic diversity between H. sericea and H. teretifolia was revealed, consistent with a contrast in their mating systems. While both species had mixed mating systems, H. sericea was found to be habitually selfing, while H. teretifolia more evenly employed both selfing and outcrossing. In both species, seed collection schemes maximised genetic diversity by increasing the number of maternal lines and sites sampled, but twice as many sites were needed for the selfing species to capture equivalent levels of genetic variation at a regional scale.
Fabrication of Sustained Release Curcumin-Loaded Solid Lipid Nanoparticles (Cur-SLNs) as a Potential Drug Delivery System for the Treatment of Lung Cancer: Optimization of Formulation and In Vitro Biological Evaluation
Authors: Rahman Mohammad Akhlaquer , Ali Abuzer , Rahamathulla Mohamed , Salam Shahana , Hani Umme , Wahab Shadma , Warsi Musarrat Husain , Yusuf Mohammad , Ali Amena , Mittal Vineet , Harwansh Ranjit Kumar
Published: January 2023

The goal of current research was to develop a new form of effective drug, curcumin-loaded solid lipid nanoparticles (Cur-SLNs) and test its efficacy in the treatment of lung cancer. Different batches of SLNs were prepared by the emulsification–ultrasonication method. For the optimization of formulation, each batch was evaluated for particle size, polydispersity index (PI), zeta potential (ZP), entrapment efficiency (EE) and drug loading (DL). The formulation components and process parameters largely affected the quality of SLNs. The SLNs obtained with particle size, 114.9 ± 1.36 nm; PI, 0.112 ± 0.005; ZP, −32.3 ± 0.30 mV; EE, 69.74 ± 2.03%, and DL, 0.81 ± 0.04% was designated as an optimized formulation. The formulation was freeze-dried to remove excess water to improve the physical stability. Freeze-dried Cur-SLNs showed 99.32% of drug release and demonstrated a burst effect trailed by sustained release up to 120 h periods. The erythrocyte toxicity study of Cur-SLNs and its components demonstrated moderate hemolytic potential towards red blood cells (RBCs). The cytotoxic potential of the formulation and plain curcumin was estimated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay against A549 cell line. After 48 h of incubation, Cur-SLNs demonstrated more cytotoxicity (IC50 = 26.12 ± 1.24 µM) than plain curcumin (IC50 = 35.12 ± 2.33 µM). Moreover, the cellular uptake of curcumin was found to be significantly higher from Cur-SLNs (682.08 ± 6.33 ng/µg) compared to plain curcumin (162.4 ± 4.2 ng/µg). Additionally, the optimized formulation was found to be stable over the period of 90 days of storage. Hence, curcumin-loaded SLNs can be prepared using the proposed cost effective method, and can be utilized as an effective drug delivery system for the treatment of lung cancer, provided in vivo studies warrant a similar outcome.
Advances in Bioinspired Superhydrophobic Surfaces Made from Silicones: Fabrication and Application
Authors: Li Zhe , Wang Xinsheng , Bai Haoyu , Cao Moyuan
Published: January 2023

As research on superhydrophobic materials inspired by the self-cleaning and water-repellent properties of plants and animals in nature continues, the superhydrophobic preparation methods and the applications of superhydrophobic surfaces are widely reported. Silicones are preferred for the preparation of superhydrophobic materials because of their inherent hydrophobicity and strong processing ability. In the preparation of superhydrophobic materials, silicones can both form micro-/nano-structures with dehydration condensation and reduce the surface energy of the material surface because of their intrinsic hydrophobicity. The superhydrophobic layers of silicone substrates are characterized by simple and fast reactions, high-temperature resistance, UV resistance, and anti-aging. Although silicone superhydrophobic materials have the disadvantages of relatively low mechanical stability, this can be improved by the rational design of the material structure. Herein, we summarize the superhydrophobic surfaces made from silicone substrates, including the cross-linking processes of silicones through dehydration condensation and hydrosilation, and the surface hydrophobic modification by grafting hydrophobic silicones. The applications of silicone-based superhydrophobic surfaces have been introduced such as self-cleaning, corrosion resistance, oil–water separation, etc. This review article should provide an overview to the bioinspired superhydrophobic surfaces of silicone-based materials, and serve as inspiration for the development of polymer interfaces and colloid science.
Analytical Determination of Cephalosporin Antibiotics Using Coordination Polymer Based on Cobalt Terephthalate as a Sorbent
Authors: Chernomorova Maria A. , Myakinina Marina S. , Zhinzhilo Vladimir A. , Uflyand Igor E.
Published: January 2023

In this work, a coordination polymer based on cobalt terephthalate was obtained and characterized by elemental analysis, infrared spectroscopy, X-ray diffraction analysis, and scanning electron microscopy. The coordination polymer was tested as a sorbent for the solid-phase extraction of cephalosporin antibiotics, including ceftriaxone, cefotaxime, and cefazolin, from aqueous solutions. The coordination polymer had a high adsorption capacity (520.0 mg/g). Antibiotics adsorption followed pseudo-second order kinetic model and the Freundlich isotherm model. The calculated thermodynamic parameters indicate a spontaneous process. The resulting coordination polymer has good stability and reusability. The possibility of separating the studied cephalosporins on a chromatographic column filled with a coordination polymer was shown. This work opens great prospects for the development and application of a coordination polymer based on cobalt terephthalate for the removal of cephalosporins from ambient water.
Case Study on Prestressed CFRP Plates Applied for Strengthening Hollow-Section Beam Removed from an Old Bridge
Authors: Liu Guirong , Li Bingchen , Bao Jiasheng , Cheng Shengzhao , Meng Qingxin , Zhao Shunbo
Published: January 2023

With the wide application of carbon fiber reinforced polymer (CFRP) plate, used for strengthening existed concrete structures, the prestressing technology of CFRP plate is becoming a hot topic, in order to sufficiently develop its high-strength peculiarity. In this paper, a full-scale hollow-section beam with length of 16 m taken from an old bridge which was in service for about 20 years was first examined for existed cracks and repaired by filling epoxy adhesive, and then the beam was strengthened with prestressed CFRP plates. The CFRP plates were tensioned and fixed with flat-plate anchorages at ends and bonded with adhesive on the bottom surface of the beam. The strengthened beam was experimentally studied using a four-point test to measure the concrete strain along the height of the mid-span section and the mid-span deflection. The finite element model of the strengthened beam was verified by the comparison of test results and used for an extending study of parametric analysis considering the effect of the length and amount of CFRP plates. Results indicated that with an increase in the length and amount of CFRP plates, the mid-span deflection of the beam decreases with the increased cracking resistance and bearing capacity, while the ultimate failure mode transfers from the under-reinforcement to the over-reinforcement.
Local and Global Order in Dense Packings of Semi-Flexible Polymers of Hard Spheres
Authors: Martínez-Fernández Daniel , Herranz Miguel , Foteinopoulou Katerina , Karayiannis Nikos Ch. , Laso Manuel
Published: January 2023

The local and global order in dense packings of linear, semi-flexible polymers of tangent hard spheres are studied by employing extensive Monte Carlo simulations at increasing volume fractions. The chain stiffness is controlled by a tunable harmonic potential for the bending angle, whose intensity dictates the rigidity of the polymer backbone as a function of the bending constant and equilibrium angle. The studied angles range between acute and obtuse ones, reaching the limit of rod-like polymers. We analyze how the packing density and chain stiffness affect the chains’ ability to self-organize at the local and global levels. The former corresponds to crystallinity, as quantified by the Characteristic Crystallographic Element (CCE) norm descriptor, while the latter is computed through the scalar orientational order parameter. In all cases, we identify the critical volume fraction for the phase transition and gauge the established crystal morphologies, developing a complete phase diagram as a function of packing density and equilibrium bending angle. A plethora of structures are obtained, ranging between random hexagonal closed packed morphologies of mixed character and almost perfect face centered cubic (FCC) and hexagonal close-packed (HCP) crystals at the level of monomers, and nematic mesophases, with prolate and oblate mesogens at the level of chains. For rod-like chains, a delay is observed between the establishment of the long-range nematic order and crystallization as a function of the packing density, while for right-angle chains, both transitions are synchronized. A comparison is also provided against the analogous packings of monomeric and fully flexible chains of hard spheres.
Preparation and Performance of Biodegradable Poly(butylene adipate-co-terephthalate) Composites Reinforced with Novel AgSnO2 Microparticles for Application in Food Packaging
Authors: Venkatesan Raja , Alagumalai Krishnapandi , Kim Seong-Cheol
Published: January 2023

Biodegradable composites with antimicrobial properties were prepared with microparticles of silver stannate (AgSnO2) and poly(butylene adipate-co-terephthalate) (PBAT) and tested for applications in food packaging. The PBAT matrix was synthesized and confirmed by 1H-nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, and X-ray diffraction (XRD). Ultrasonic and coprecipitation methods were used to synthesize AgSnO2. A two-step mixing method and a solvent cast technique were utilized to fabricate the PBAT composites (different weight % of AgSnO2) for packaging foods. Attenuated total reflection-infrared spectroscopy, X-ray photoelectron spectroscopy, XRD, and scanning electron microscopy were used to investigate the formation, structure, and size of the composites. Thermogravimetric analysis and differential thermal calorimetry were used to examine the PBAT/AgSnO2 composites. The best characteristics are exhibited in 5.0 wt. % AgSnO2 loaded PBAT composite. The tensile strength, elongation at break, water vapor transmission rate, and oxygen transmission rate were 22.82 MPa, 237.00%, 125.20 g/m2/day, and 1104.62 cc/m2/day.atm, respectively. Incorporating AgSnO2 enhanced the hydrophobicity of the PBAT materials as evaluated by the water contact angle. The 5.0 wt. % AgSnO2/PBAT film shows a favorable zone of inhibition against the bacteria pathogens S. aureus and E. coli, according to an evaluation of its antimicrobial activity. The weight loss of 5% AgSnO2/PBAT film was 78.4% after eight weeks in the natural soil environments. In addition, the results of food quality studies recommend that AgSnO2/PBAT (5.0 wt. %) film had a longer food shelf life than the neat PBAT and commercial, increasing it from one to 14 days for carrot vegetables.
The Current Status, Prospects, and Challenges of Shape Memory Polymers Application in Bone Tissue Engineering
Authors: Li Tingting , Chen Liang , Yuan Yu , Shi Rengfei
Published: January 2023

Bone defects can occur after severe trauma, infection, or bone tumor resection surgery, which requires grafting to repair the defect when it reaches a critical size, as the bone’s self-healing ability is insufficient to complete the bone repair. Natural bone grafts or artificial bone grafts, such as bioceramics, are currently used in bone tissue engineering, but the low availability of bone and high cost limit these treatments. Therefore, shape memory polymers (SMPs), which combine biocompatibility, biodegradability, mechanical properties, shape tunability, ease of access, and minimally invasive implantation, have received attention in bone tissue engineering in recent years. Here, we reviewed the various excellent properties of SMPs and their contribution to bone formation in experiments at the cellular and animal levels, respectively, especially for the repair of defects in craniomaxillofacial (CMF) and limb bones, to provide new ideas for the application of these new SMPs in bone tissue engineering.
Assessing the Impact and Suitability of Dense Carbon Dioxide as a Green Solvent for the Treatment of PMMA of Historical Value
Authors: Bartoletti Angelica , Soares Inês , Ramos Ana Maria , Shashoua Yvonne , Quye Anita , Casimiro Teresa , Ferreira Joana Lia
Published: January 2023

Surface cleaning of plastic materials of historical value can be challenging due to the high risk of inducing detrimental effects and visual alterations. As a result, recent studies have focused on researching new approaches that might reduce the associated hazards and, at the same time, minimize the environmental impact by employing biodegradable and green materials. In this context, the present work investigates the effects and potential suitability of dense carbon dioxide (CO2) as an alternative and green solvent for cleaning plastic materials of historical value. The results of extensive trials with CO2 in different phases (supercritical, liquid, and vapor) and under various conditions (pressure, temperature, exposure, and depressurization time) are reported for new, transparent, thick poly(methyl methacrylate) (PMMA) samples. The impact of CO2 on the weight, the appearance of the samples (dimensions, color, gloss, and surface texture), and modifications to their physicochemical and mechanical properties were monitored via a multi-analytical approach that included optical microscopy, Raman and attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopies, and micro-indentation (Vickers hardness). Results showed that CO2 induced undesirable and irreversible changes in PMMA samples (i.e., formation of fractures and stress-induced cracking, drastic decrease in the surface hardness of the samples), independent of the conditions used (i.e., temperature, pressure, CO2 phase, and exposure time).
Study on Shear Behaviors and Damage Assessment of Circular Concrete Short Columns Reinforced with GFRP Bars and Spiral Stirrups
Authors: Wang Xiaolu , Zhou Lingzhu , Liang Yuke , Zheng Yu , Li Lixiao , Di Bo
Published: January 2023

This study investigated the shear resistance and damage evolution of glass fiber-reinforced polymer (GFRP)-reinforced concrete short columns. Five circular concrete short columns reinforced with GFRP bars and spiral stirrups were fabricated and tested under lateral thrust in the laboratory. The test variables involved the stirrup reinforcement ratio, the longitudinal reinforcement ratio and the type of stirrups. The failure modes, load-displacement curves, strain responses and crack characteristics of these columns were documented and discussed. The accuracy of shear design equations in predicting shear capacity of such columns was evaluated. In addition, the digital image correlation (DIC) instrument was used to identify the full-field strain and damage zones of circular concrete short columns. Several smart aggregate (SA) transducers coupled to the surface of these columns were used to monitor its damage status. The energy ratio index (ERI) and the damage index based on smart aggregate were established to characterize damage level of such columns. The test results indicate that the shear capacity is improved 5.6% and 31.1% and the lateral ultimate displacement is increased 67.7% and 400% as the stirrup reinforcement ratio of the concrete short column is increased from 0 to 0.19% and 0.47%, respectively. The shear capacity equation proposed by Ali and his co-workers, considering a strain limit of 0.004Efv, gives accurate predictions of the shear capacity of circular concrete short columns reinforced with GFRP bars and spiral stirrups. The variation in ERI values is explained by the development of damage zones of the column obtained with DIC technology and with the proposed damage index based on the smart aggregate it is feasible to evaluate the damage level of circular short concrete columns.
Development and Evaluation of Cellulose/Graphene-Oxide Based Composite for Removing Phenol from Aqueous Solutions
Authors: Kumar Naveen , Kumar Bijender , Gupta Himanshu , Kumar Anuj
Published: January 2023

In this study, a graphene oxide/cellulose composite (GO–cellulose) was prepared usingcellulose and graphene oxide (GO) through ultrasonication, followed by the freeze-dried method. The Brunauer–Emmett–Teller (BET) specific surface area of GO–cellulose (~6.042 m2/g) was higher compared to cellulose (1.023 m2/g).The UV-Visible spectraindicated that the prepared GO–cellulose composite removedphenol efficiently from aqueous solutions with high adsorption power. The effectiveness of the composite for phenol adsorption was examinedunder diverse conditions.The results reveal that the composite optimally improved the adsorption at pH 7 with a dose of 0.125 g/30 L in about 40 min. The adsorption process showed that in optimum conditions, 86 ± 2% of phenol was removed in 40 min with an adsorption capacity of 6.192 mg g−1. The adsorption behavior was well fitted to the pseudo-second-order kinetic model and the Langmuir isotherms at all temperatures.The present study suggests that synthesized GO–cellulose is useful inthe removal of phenol pollutants from aqueous solutions.
Evaluation of Selected Cellulose Macromolecular Properties after Its Chemical Treatment Using Size Exclusion Chromatography
Authors: Jurczyková Tereza , Kačík František , Čabalová Iveta , Hájková Kateřina
Published: January 2023

This work evaluates the effect of using selected inorganic chemicals as the main components of waterborne wood preservative systems on the degradation of the cellulose constituent in wood from model samples. The polymeric properties of cellulose and the homogeneity of the degradation process primarily reflect very well the degree of cellulose deterioration. Whatman papers, as pure cellulose model samples, were impregnated with 10 different 5 wt% solutions of inorganic salts and distilled water and consequently subjected to wet-thermal accelerated aging (T = 85 °C, RH = 65%, for 30 days). The samples were then derivatized to cellulose tricarbanilates (CTCs) through two different procedures (by precipitation in a methanol–water mixture/by evaporation of pyridine from the reaction mixture) and finally analyzed using size exclusion chromatography (SEC). Chemically treated and aged cellulose samples showed different changes in the degree of polymerization (DP) and polydispersity (PD) in terms of untreated non-aged standard caused by different ongoing degradation reactions, such as dehydration, hydrolysis, oxidation, and crosslinking. In general, the lowest degradation rate after treatment by chemicals and after accelerated aging was observed in samples treated by borates, NaCl, and ZnSO4·7H2O. The greatest depolymerization after treatment and after accelerated aging was caused by sulphates containing NH4+, Cu2+, and Fe3+ cations, with aging by NH4Cl and (NH4)2HPO4-treated samples also leading to significant depolymerization. The higher DP values are linked to the precipitated method of CTC preparation, though not for chlorides and phosphates. PD is also generally higher in precipitated and aged samples and is heavily influenced by the presence of low molecular weight products. This paper brings new insights regarding the complex evaluation of the polymeric properties of degraded cellulose by considering all important factors affecting the sample and the analysis itself through the use of statistics. From the statistical point of view, the influences of all factors (solution, aging, method) and their interactions (except aging*method) on DP are statistically significant. The influence of the sample processing method used for analysis of the desired results becomes important mainly in practice. This work recommends the evaporation method for more accurate description of more degraded cellulose.
Starch Chemical Composition and Molecular Structure in Relation to Physicochemical Characteristics and Resistant Starch Content of Four Thai Commercial Rice Cultivars Differing in Pasting Properties
Authors: Sangwongchai Wichian , Tananuwong Kanitha , Krusong Kuakarun , Natee Supidcha , Thitisaksakul Maysaya
Published: January 2023

Variations in starch pasting properties, considered an alternative potential quality classification parameter for rice starches, are directly controlled by the diverse starch molecular composition and structural features. Here, the starch characteristics of four rice cultivars (i.e., RD57, RD29, KDML105, and RD6) differing in pasting properties were assessed, and their relationship was determined. The results revealed that protein and moisture contents and their crystalline type were similar among the four rice starches. However, their molecular compositions and structures (i.e., reducing sugar and amylose contents, amylopectin branch chain-length distributions, granule size and size distribution, and degree of crystallinity) significantly varied among different genotypes, which resulted in distinct swelling, solubility, gelatinization, retrogradation, and hydrolytic resistance properties. The swelling power and gelatinization enthalpy (∆H) were positively correlated with C-type granule and relative crystallinity, but were negatively correlated with amylose content, B-type granule and median particle size (d(0.5)). Conversely, the water solubility and resistant starch content negatively correlated with C-type granule, but positively correlated with amylose content, B-type granule, and d(0.5). The gelatinization onset temperature (To(g)), and retrogradation concluding temperatures (Tc(r)), enthalpy (∆H(r)), and percentage (R%) were positively impacted by the amount of protein, amylose, and B1 chains (DP 13–24), while they were negatively correlated with short A chains (DP 6–12). Collectively, the starch physicochemical and functional properties of these Thai rice starches are attributed to an interplay between compositional and structural features. These results provide decisive and crucial information on rice cultivars’ suitability for consumption as cooked rice and for specific industrial applications.
3D-Printed Polycaprolactone Mechanical Characterization and Suitability Assessment for Producing Wrist–Hand Orthoses
Authors: Popescu Diana , Stochioiu Constantin , Baciu Florin , Iacob Mariana Cristiana
Published: January 2023

In this research, the mechanical properties of 3D-printed polycaprolactone (PCL), a biocompatible and biodegradable semi-crystalline polyester, available as feedstock for additive manufacturing technology based on the material extrusion process, were determined. The influence of the infill pattern (zig-zag vs. gyroid) and ultraviolet (UV-B) exposure over the specimens’ mechanical performances were also investigated to gather relevant data on the process parameter settings for different applications. Specimens and samples of 3D-printed PCL were analyzed through tensile and flexural tests. The experimental data showed the good repeatability of the manufacturing process, as well as a mechanical behavior independent of the specimens’ infill pattern at full density. No differences between the failure patterns of the tensile specimens were recorded. UV-B exposure proved to have a significant negative impact on the specimens’ tensile strength. The 3D printing of PCL and PCL blends is reported mainly for use in scaffold manufacturing or drug delivery applications. As another novelty, the suitability of commercial PCL filaments for producing patient-customized wrist–hand orthoses was also assessed in this study. Semi-cylindrical PCL samples mimicking the forearm part of a wrist–hand orthosis with hexagonal open pockets were 3D-printed and mechanically tested. The results were discussed in comparison to samples with a similar design, made of polylactic acid. The experiments revealed the need to carefully calibrate the manufacturing parameters to generate defect-free, good quality prints. Once settings were established, promising results were obtained when producing orthoses in a ready-to-use form. On the other hand, the attempts to thermoform flat 3D-printed PCL orthoses proved unsuccessful.
Development of Polydiphenylamine@Electrochemically Reduced Graphene Oxide Electrode for the D-Penicillamine Sensor from Human Blood Serum Samples Using Amperometry
Authors: Ranjith Kumar Deivasigamani , Rajesh Kuppusamy , Sayed Mostafa Saad , Milton Ahamed , Shim Jae-Jin
Published: January 2023

D-penicillamine (PA) is a sulfur group-containing drug prescribed for various health issues, but overdoses have adverse effects. Therefore, regular, selective, and sensitive sensing is essential to reduce the need for further treatment. In this study, diphenylamine (DPA) was electropolymerized in an aqueous acidic medium. The PA detection sensitivity, selectivity, and limit of detection were enhanced by electropolymerizing DPA on an electrochemically reduced graphene oxide (ERGO)/glassy carbon (GC) surface. The formation of p-DPA and ERGO was investigated using various techniques. The as-prepared p-DPA@ERGO/GC revealed the excellent redox-active (N–C to N=C) sites of p-DPA. The p-DPA@ERGO/GC electrode exhibited excellent electrochemical sensing ability towards PA determination because of the presence of the –NH–functional moiety and effective interactions with the –SH group of PA. The p-DPA@ERGO/GC exhibited a high surface coverage of 9.23 × 10−12 mol cm−2. The polymer-modified p-DPA@ERGO/GC electrode revealed the amperometric determination of PA concentration from the 1.4 to 541 μM wide range and the detection limit of 0.10 μM. The real-time feasibility of the developed p-DPA@ERGO/GC electrode was tested with a realistic PA finding in human blood serum samples and yielded a good recovery of 97.5–101.0%, confirming the potential suitability in bio-clinical applications.
Study on the Hydrodynamic Performance of a Countercurrent Total Spray Tray under Sloshing Conditions
Authors: Tao Jinliang , Zhang Guangwei , Yao Jiakang , Wang Leiming , Wei Feng
Published: January 2023

In this paper, a new type of total spray tray (TST) with gas–liquid countercurrent contact is proposed to solve the problem of slight operation flexibility and poor sloshing resistance in towers under offshore conditions. Its hydrodynamic performance indicators, such as pressure drop, weeping, entrainment, and liquid level unevenness, were experimentally studied under rolling motion. A tower with an inner diameter of 400 mm and tray spacing of 350 mm was installed on a sloshing platform to simulate offshore conditions. The experimental results show that the rolling motion affected the hydrodynamic performance of the tray under experimental conditions. When the rolling amplitude did not exceed 4°, the degree of fluctuation of the hydrodynamic performance was small, and the tray could still work stably. With increasing rolling amplitude, the TST wet plate pressure drop, weeping, and liquid level unevenness fluctuations also increased. When the rolling amplitude reached 7°, the maximum fluctuation of the wet plate pressure drop was 8.9% compared to that in the static state, and the plate hole kinetic energy factor, as the TST reached the lower limit of weeping, increased rapidly from 6.2 at rest to 7.8 under the experimental conditions. It can be seen that the TST still exhibits good hydrodynamic performance under rolling motion.
SAR Image Classification Using Markov Random Fields with Deep Learning
Authors: Yang Xiangyu , Yang Xuezhi , Zhang Chunju , Wang Jun
Published: January 2023

Classification algorithms integrated with convolutional neural networks (CNN) display high accuracies in synthetic aperture radar (SAR) image classification. However, their consideration of spatial information is not comprehensive and effective, which causes poor performance in edges and complex regions. This paper proposes a Markov random field (MRF)-based algorithm for SAR image classification which fully considers the spatial constraints between superpixel regions. Firstly, the initialization of region labels is obtained by the CNN. Secondly, a probability field is constructed to improve the distribution of spatial relationships between adjacent superpixels. Thirdly, a novel region-level MRF is employed to classify the superpixels, which combines the intensity field and probability field in one framework. In our algorithm, the generation of superpixels reduces the misclassification at the pixel level, and region-level misclassification is rectified by the improvement of spatial description. Experimental results on simulated and real SAR images confirm the efficacy of the proposed algorithm for classification.
Variability of Glacier Velocity and the Influencing Factors in the Muztag-Kongur Mountains, Eastern Pamir Plateau
Authors: Huang Danni , Zhang Zhen , Jiang Ling , Zhang Rui , Lu Yijie , Shahtahmassebi AmirReza , Huang Xiaoli
Published: January 2023

Glacier velocity is the key to understanding the nature of glaciers. Its variation plays an important role in glacier dynamics, mass balance, and climate change. The Muztag-Kongur Mountains are an important glacier region in the Eastern Pamir Plateau. Under the background of global warming, the glacier velocity variation has been widely considered, but details of the inter-annual and intra-annual changes have not been clear. In this study, we explored the inter-annual and intra-annual variations in the glacier velocity from 1990 to 2021, and the influencing factors, based on Landsat images, Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE), and Karakoram Highway (KKH) data product analysis. The results showed the following: (1) the glacier velocity has increased since 1990, and significant growth occurred in 1995–1996. (2) A transverse profile of two typical glaciers was used to analyze the monthly variation in glacier velocity during the year. The peaks of monthly velocity occurred in May and August. (3) Since 1990, the inter-annual precipitation has increased, and the temperature increase slowed down from 2000 to 2013. The trend of inter-annual glacier velocity variation was consistent with that of the precipitation. The glacier velocity peaked in 1996/1997 due to increased precipitation in 1995. The glacier velocity over the year was consistent with the monthly precipitation trends, which indicates that precipitation has a significant influence on the change in glacier velocity. (4) In addition to temperature and precipitation, the glacier velocity variation was moderately correlated with the glacier size (length and area) and weakly correlated with the slope. The spatial distribution of glaciers shows that the spatial heterogeneity of glaciers in the Muztag-Kongur Mountains is affected by the westerly circulation. The long-term glacier velocity variation research of the Muztag-Kongur Mountains will contribute to a better understanding of glacier dynamics within the context of climatic warming, and the different influencing factors were analyzed to further explain the glacier velocity variation.
Spatiotemporal Distribution Pattern and Driving Factors Analysis of GPP in Beijing-Tianjin-Hebei Region by Long-Term MODIS Data
Authors: Guo Heyi , Cao Chunxiang , Xu Min , Yang Xinwei , Chen Yiyu , Wang Kaimin , Duerler Robert Shea , Li Jingbo , Gao Xiaotong
Published: January 2023

Gross primary productivity (GPP) is an important parameter that represents the productivity of vegetation and responses to various ecological environments. Using the Mann–Kendall methods, Pearson correlation, and the Geodetector, this study investigated the spatiotemporal variation and driving factors of GPP from 2000 to 2020. The results showed that (1) in terms of spatial distribution, GPP showed a trend of “low-high-low” regions, with low values for grassland and arable land and a high value for forest land. The growth trend is fast in forest areas, while the growth trend is not obvious in cultivated areas. The regions with significant growth accounted for 68.73% of the whole region. (2) The whole region shows a growth rate of 2.07 g C∙m−2∙yr−1, showing obvious seasonality, with a slow growth trend in spring and autumn and a fast growth trend in summer. (3) The driving factors of GPP spatial differentiation in the Beijing-Tianjin-Hebei region were land surface temperature, land use type, and nighttime light data, while precipitation and downward surface shortwave radiation show no strong explanatory power for the spatial differentiation of GPP, which means that these two factors have less driving force on the spatial differentiation of GPP. The interaction of LUCC with the other factors presents two-factor enhancement, while the LST interaction with the other three factors presents non-linear enhancement. This study could provide a theoretical basis for the sustainable development of the Beijing-Tianjin-Hebei Region.
Monitoring of 35-Year Mangrove Wetland Change Dynamics and Agents in the Sundarbans Using Temporal Consistency Checking
Authors: Zhang Zhen , Ahmed Md Rasel , Zhang Qian , Li Yi , Li Yangfan
Published: January 2023

Mangrove wetlands are rapidly being lost due to anthropogenic disturbances and natural processes, such as sea-level rise (SLR), but are also recovering as a result of conservation efforts. Accurate and contemporary mangrove maps to detect their distribution and changes are urgently needed to understand how mangroves respond to global change and develop effective conservation projects. Here, we developed a new change detection algorithm called temporal consistency checking combining annual classification and spectral time series (TCC-CS) for tracking mangrove losses and gains. Specifically, mangrove change events were determined by measuring the deviation of greenness and wetness of candidate change segments from automatically collected mangrove reference samples. By applying to the world’s largest mangrove patches, we monitored the 35-year mangrove trajectory in the Sundarbans from 1988 to 2022 using all available Landsat images on the Google Earth Engine platform. In the Sundarbans, 18,501.89 ha of mangroves have been gained, but these have been offset by losses of 27,009.79 ha, leading to a net mangrove loss of 1.42% (8507.9 ha) in the past 35 years. We further mapped the pixel-level change agents and found that SLR-induced erosion and degradation, instead of human activities, were the major drivers of losses in the Sundarbans. Trend analysis on loss agents indicates that mangrove losses caused by human activities, such as the expansion of croplands and aquaculture ponds, have declined, but SLR is still a persistent threat to mangrove wetlands in this iconic mangrove area. Our study provides a computationally efficient methodology for examining large-scale mangrove changes, and the resultant annual mangrove maps provide strong support for mangrove conservation in the Sundarbans.
D-MFPN: A Doppler Feature Matrix Fused with a Multilayer Feature Pyramid Network for SAR Ship Detection
Authors: Zhou Yucheng , Fu Kun , Han Bing , Yang Junxin , Pan Zongxu , Hu Yuxin , Yin Di
Published: January 2023

Ship detection from synthetic aperture radar (SAR) images has become a major research field in recent years. It plays a major role in monitoring the ocean, marine rescue activities, and marine safety warnings. However, there are still some factors that restrict further improvements in detecting performance, e.g., multi-scale ship transformation and unfocused images caused by motion. In order to resolve these issues, in this paper, a doppler feature matrix fused with a multi-layer feature pyramid network (D-MFPN) is proposed for SAR ship detection. The D-MFPN takes single-look complex image data as input and consists of two branches: the image branch designs a multi-layer feature pyramid network to enhance the positioning capacity for large ships combined with an attention module to refine the feature map’s expressiveness, and the doppler branch aims to build a feature matrix that characterizes the ship’s motion state by estimating the doppler center frequency and frequency modulation rate offset. To confirm the validity of each branch, individual ablation experiments are conducted. The experimental results on the Gaofen-3 satellite ship dataset illustrate the D-MFPN’s optimal performance in defocused ship detection tasks compared with six other competitive convolutional neural network (CNN)-based SAR ship detectors. Its satisfactory results demonstrate the application value of the deep-learning model fused with doppler features in the field of SAR ship detection.
Dynamic Detection of Forest Change in Hunan Province Based on Sentinel-2 Images and Deep Learning
Authors: Xiang Jun , Xing Yuanjun , Wei Wei , Yan Enping , Jiang Jiawei , Mo Dengkui
Published: January 2023

Dynamic detection of forest change is the fundamental method of monitoring forest resources and an essential means of preserving the accuracy and timeliness of forest land resource data. This study focuses on a deep learning-based method for dynamic forest change detection using Sentinel-2 satellite data, especially within mountainous areas. First, the performance of various deep learning models (U-Net++, U-Net, LinkNet, DeepLabV3+, and STANet) and various loss functions (CrossEntropyLoss(CELoss), DiceLoss, FocalLoss, and their combinations) are compared on a self-made dataset. Next, the best model and loss function is used to predict the annual forest change in Hunan Province from 2017 to 2021, and the detection results are evaluated in 12 sample areas. Finally, forest changes are detected in Sentinel-2 images for each quarter of 2017–2021. In addition, a dynamic detection map of forest change in Hunan Province from 2017 to 2021 is drawn. The results reveal that the U-Net++ model and the CELoss performed the best on the self-made dataset, with a Precision of 0.795, a Recall of 0.748, and an F1-score of 0.771. The results of annual and quarterly forest change detection were consistent with the changes in the Sentinel-2 images with accurate boundaries. This result demonstrates the high practicality and generalizability of the method used in this paper. This paper achieves a rapid and accurate extraction of multi-temporal Sentinel-2 image forest change areas based on the U-Net++ model, which can be used as a benchmark for future large territorial areas monitoring and management of forest resources.
Scale in Scale for SAR Ship Instance Segmentation
Authors: Shao Zikang , Zhang Xiaoling , Wei Shunjun , Shi Jun , Ke Xiao , Xu Xiaowo , Zhan Xu , Zhang Tianwen , Zeng Tianjiao
Published: January 2023

Ship instance segmentation in synthetic aperture radar (SAR) images can provide more detailed location information and shape information, which is of great significance for port ship scheduling and traffic management. However, there is little research work on SAR ship instance segmentation, and the general accuracy is low because the characteristics of target SAR ship task, such as multi-scale, ship aspect ratio, and noise interference, are not considered. In order to solve these problems, we propose an idea of scale in scale (SIS) for SAR ship instance segmentation. Its essence is to establish multi-scale modes in a single scale. In consideration of the characteristic of the targeted SAR ship instance segmentation task, SIS is equipped with four tentative modes in this paper, i.e., an input mode, a backbone mode, an RPN mode (region proposal network), and an ROI mode (region of interest). The input mode establishes multi-scale inputs in a single scale. The backbone mode enhances the ability to extract multi-scale features. The RPN mode makes bounding boxes better accord with ship aspect ratios. The ROI mode expands the receptive field. Combined with them, a SIS network (SISNet) is reported, dedicated to high-quality SAR ship instance segmentation on the basis of the prevailing Mask R-CNN framework. For Mask R-CNN, we also redesign (1) its feature pyramid network (FPN) for better small ship detection and (2) its detection head (DH) for a more refined box regression. We conduct extensive experiments to verify the effectiveness of SISNet on the open SSDD and HRSID datasets. The experimental results reveal that SISNet surpasses the other nine competitive models. Specifically, the segmentation average precision (AP) index is superior to the suboptimal model by 4.4% on SSDD and 2.5% on HRSID.
Hot Exoplanetary Atmospheres in 3D
Authors: Pluriel William
Published: January 2023

Hot giant exoplanets are very exotic objects with no equivalent in the Solar System that allow us to study the behavior of atmospheres under extreme conditions. Their thermal and chemical day–night dichotomies associated with extreme wind dynamics make them intrinsically 3D objects. Thus, the common 1D assumption, relevant to study colder atmospheres, reaches its limits in order to be able to explain hot and ultra-hot atmospheres and their evolution in a consistent way. In this review, we highlight the importance of these 3D considerations and how they impact transit, eclipse and phase curve observations. We also analyze how the models must adapt in order to remain self-consistent, consistent with the observations and sufficiently accurate to avoid bias or errors. We particularly insist on the synergy between models and observations in order to be able to carry out atmospheric characterizations with data from the new generation of instruments that are currently in operation or will be in the near future.
Fusion of VNIR Optical and C-Band Polarimetric SAR Satellite Data for Accurate Detection of Temporal Changes in Vegetated Areas
Authors: Alparone Luciano , Garzelli Andrea , Zoppetti Claudia
Published: January 2023

In this paper, we propose a processing chain jointly employing Sentinel-1 and Sentinel-2 data, aiming to monitor changes in the status of the vegetation cover by integrating the four 10 m visible and near-infrared (VNIR) bands with the three red-edge (RE) bands of Sentinel-2. The latter approximately span the gap between red and NIR bands (700 nm–800 nm), with bandwidths of 15/20 nm and 20 m pixel spacing. The RE bands are sharpened to 10 m, following the hyper-sharpening protocol, which holds, unlike pansharpening, when the sharpening band is not unique. The resulting 10 m fusion product may be integrated with polarimetric features calculated from the Interferometric Wide (IW) Ground Range Detected (GRD) product of Sentinel-1, available at 10 m pixel spacing, before the fused data are analyzed for change detection. A key point of the proposed scheme is that the fusion of optical and synthetic aperture radar (SAR) data is accomplished at level of change, through modulation of the optical change feature, namely the difference in normalized area over (reflectance) curve (NAOC), calculated from the sharpened RE bands, by the polarimetric SAR change feature, achieved as the temporal ratio of polarimetric features, where the latter is the pixel ratio between the co-polar and the cross-polar channels. Hyper-sharpening of Sentinel-2 RE bands, calculation of NAOC and modulation-based integration of Sentinel-1 polarimetric change features are applied to multitemporal datasets acquired before and after a fire event, over Mount Serra, in Italy. The optical change feature captures variations in the content of chlorophyll. The polarimetric SAR temporal change feature describes depolarization effects and changes in volumetric scattering of canopies. Their fusion shows an increased ability to highlight changes in vegetation status. In a performance comparison achieved by means of receiver operating characteristic (ROC) curves, the proposed change feature-based fusion approach surpasses a traditional area-based approach and the normalized burned ratio (NBR) index, which is widespread in the detection of burnt vegetation.
A Review of Estimation Methods for Aboveground Biomass in Grasslands Using UAV
Authors: Bazzo Clara Oliva Gonçalves , Kamali Bahareh , Hütt Christoph , Bareth Georg , Gaiser Thomas
Published: January 2023

Grasslands are one of the world’s largest ecosystems, accounting for 30% of total terrestrial biomass. Considering that aboveground biomass (AGB) is one of the most essential ecosystem services in grasslands, an accurate and faster method for estimating AGB is critical for managing, protecting, and promoting ecosystem sustainability. Unmanned aerial vehicles (UAVs) have emerged as a useful and practical tool for achieving this goal. Here, we review recent research studies that employ UAVs to estimate AGB in grassland ecosystems. We summarize different methods to establish a comprehensive workflow, from data collection in the field to data processing. For this purpose, 64 research articles were reviewed, focusing on several features including study site, grassland species composition, UAV platforms, flight parameters, sensors, field measurement, biomass indices, data processing, and analysis methods. The results demonstrate that there has been an increase in scientific research evaluating the use of UAVs in AGB estimation in grasslands during the period 2018–2022. Most of the studies were carried out in three countries (Germany, China, and USA), which indicates an urgent need for research in other locations where grassland ecosystems are abundant. We found RGB imaging was the most commonly used and is the most suitable for estimating AGB in grasslands at the moment, in terms of cost–benefit and data processing simplicity. In 50% of the studies, at least one vegetation index was used to estimate AGB; the Normalized Difference Vegetation Index (NDVI) was the most common. The most popular methods for data analysis were linear regression, partial least squares regression (PLSR), and random forest. Studies that used spectral and structural data showed that models incorporating both data types outperformed models utilizing only one. We also observed that research in this field has been limited both spatially and temporally. For example, only a small number of papers conducted studies over a number of years and in multiple places, suggesting that the protocols are not transferable to other locations and time points. Despite these limitations, and in the light of the rapid advances, we anticipate that UAV methods for AGB estimation in grasslands will continue improving and may become commercialized for farming applications in the near future.