bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of Nasal-Brain-Targeting Efficiency of New Developed Mucoadhesive Emulsomes Encapsulating an Anti-Migraine Drug for Effective Treatment of One of the Major Psychiatric Disorders Symptoms
Authors: Abo El-Enin Hadel A. , Mostafa Rasha E. , Ahmed Marwa F. , Naguib Ibrahim A. , A. Abdelgawad Mohamed , Ghoneim Mohammed M. , Abdou Ebtsam M.
Published: February 2022

Migraine is one of the major symptoms of many psychiatric and mental disorders like depression and anxiety. Eletriptan Hydrobromide (EH) is a well-tolerated drug in migraine treatment, but suffers from low oral bioavailability and low brain targeting after oral delivery. New nasal mucoadhesive EH-emulsomes development could be a new means to direct the drug from the nose-to-brain to achieve rapid onset of action and high drug concentration in the brain for acute migraine treatment. Eletriptan mucoadhesive emulsomes formulations were prepared using thin-film hydration method and 23 full factorial design was adopted to study different formulation factors’ effect on the emulsomes characters. The emulsomes were characterized for entrapment efficiency (EE%), zeta potential (ZP), particle size (PS), morphology, and ex-vivo permeation through the nasal mucosa. The selected formula was evaluated in mice for its in-vivo bio-distribution in comparison with EH intranasal and intravenous solutions. Drug targeting efficacy (DTE%) and nose-to-brain direct transport percentage (DTP%) were calculated. The optimization formulation showed a nanoparticle size of 177.01 nm, EE 79.44%, and ZP = 32.12 ± 3.28 mV. In addition, in-vitro permeability studies revealed enhanced drug permeability with suitable mean residence time up to 120 ± 13 min. EH-emulsomes were stable under different storage conditions for three months. In vivo examination and pharmacokinetic drug targeting parameters revealed EH transport to the CNS after EH nanoparticle nasal administration. Histopathology study showed no ciliotoxic effect on the nasal mucosa. From the results, it can be confirmed that the emulsomes formulation of EH proved safe direct nose-to-brain transport of EH after nasal administration of EH emulsomes.
Delivery of Intravenously Administered Antibodies Targeting Alzheimer’s Disease-Relevant Tau Species into the Brain Based on Receptor-Mediated Transcytosis
Authors: Tashima Toshihiko
Published: February 2022

Alzheimer’s disease (AD) is a neurodegenerative disease that causes memory loss, cognitive decline, and eventually dementia. The etiology of AD and its pathological mechanisms remain unclear due to its complex pathobiology. At the same time, the number of patients with AD is increasing worldwide. However, no therapeutic agents for AD are currently available for definitive care. Several phase 3 clinical trials using agents targeting amyloid β (Aβ) and its related molecules have failed, with the exception of aducanumab, an anti-Aβ monoclonal antibody (mAb), clinically approved by the US Food and Drug Administration in 2021, which could be modified for AD drug development due to controversial approval. Neurofibrillary tangles (NFTs) composed of tau rather than senile plaques composed of Aβ are correlated with AD pathogenesis. Moreover, Aβ and tau pathologies initially proceed independently. At a certain point in the progression of AD symptoms, the Aβ pathology is involved in the alteration and spreading of the tau pathology. Therefore, tau-targeting therapies have attracted the attention of pharmaceutical scientists, as well as Aβ-targeting therapies. In this review, I introduce the implementations and potential of AD immunotherapy using intravenously administered anti-tau and anti-receptor bispecific mAbs. These cross the blood-brain barrier (BBB) based on receptor-mediated transcytosis and are subsequently cleared by microglia based on Fc-mediated endocytosis after binding to tau and lysosomal degradation.
Discovery and Characterization of a New Crustin Antimicrobial Peptide from Amphibalanus amphitrite
Authors: Zhang Wei , Xu Xiaohang , Zhang Jun , Ye Ting , Zhou Qiao , Xu Ying , Li Wenyi , Hu Zhangli , Shang Chenjing
Published: February 2022

Crustins are an antimicrobial peptide (AMP) family that plays an important role in innate immunity in crustaceans. It is important to discover new AMPs from natural sources to expand the current database. Here, we identified and characterized a new crustin family member, named AaCrus1, from Amphibalanus amphitrite. AaCrus1 shares high identity (48.10%) with PvCrus, a Type I crustin of Penaeus vannamei that possesses a whey acidic protein (WAP) domain. AaCrus1 contains 237 amino acids and eight cysteine residues forming conserved ‘four-disulfide core’ structure. Our recombinant AaCrus1 (rAaCrus 1) could inhibit the growth of two Gram-positive bacteria (Staphylococcus aureus, Bacillus sp. T2) and four Gram-negative bacteria (Vibrio parahaemolyticus, Vibrio harveyi, Vibrio anguillarum, Vibrio alginolyticus) with a minimum inhibitory concentration of 3.5–28 μM. It can further induce agglutination of both Gram-positive and Gram-negative bacteria. rAaCrus1 can bind to bacteria and damage bacterial cell membranes. Furthermore, rAaCrus1 disrupted biofilm development of S. aureus and V. parahaemolyticus. Our discovery and characterization of this new crustin can be further optimized as a good alternative to antibiotics.
Formulation Approaches for Improving the Dissolution Behavior and Bioavailability of Tolvaptan Using SMEDDS
Authors: Lee Jong-Hwa , Lee Gye-Won
Published: February 2022

Tolvaptan, a selective vasopressin receptor antagonist, is a Class IV agent of Biopharmaceutical Classification System (BCS). To improve bioavailability after oral administration, the new tolvaptan-loaded self-microemulsifying drug delivery system (SMEDDS) was further optimized using a “design of the experiment (DoE)” including components of D-optional mixture design. Based on a solubility study of tolvaptan in various oils, surfactants, and cosurfactants, Capryol® 90, Tween 20, and Transcutol® HP [or polyethylene glycol 200 (PEG 200)] were finally selected for optimization of tolvaptan-loaded SMEDDS formulations. The fitting models of, and poly-nominal equations for, all response variables were acceptable, as revealed by analysis of variance (ANOVA, R2 > 0.900, p < 0.0001). The optimized formulations A-1 (Capryol® 90/Tween 20/Transcutol® HP = 10%/70%/20% w/w) and B-1 (Capryol® 90/Tween 20/PEG 200 = 10%/70%/20% w/w) with desirabilities of 0.905 and 1.000, respectively, showed low droplet size and the dissolution rate exceeded 95% at 15 and 60 min. The tolvaptan-loaded SMEDDS remained stable for 3 months under accelerated conditions, thus with no change in any of content, color, particle size, or dissolution rate. In a rat pharmacokinetic study, the bioavailability of formulations A-1 (16.6%) and B-1 (11.5%) were 23–33-fold higher than that of raw tolvaptan powder (0.5%). Thus, the use of “quality by design (QbD)” during development of tolvaptan-loaded SMEDDS improved the dissolution rate and oral drug bioavailability.
3D Printing of Pediatric Medication: The End of Bad Tasting Oral Liquids?—A Scoping Review
Authors: Lafeber Iris , Ruijgrok Elisabeth J. , Guchelaar Henk-Jan , Schimmel Kirsten J. M.
Published: February 2022

3D printing of pediatric-centered drug formulations can provide suitable alternatives to current treatment options, though further research is still warranted for successful clinical implementation of these innovative drug products. Extensive research has been conducted on the compliance of 3D-printed drug products to a pediatric quality target product profile. The 3D-printed tablets were of particular interest in providing superior dosing and release profile similarity compared to conventional drug manipulation and compounding methods, such as oral liquids. In the future, acceptance of 3D-printed tablets in the pediatric patient population might be better than current treatments due to improved palatability. Further research should focus on expanding clinical knowledge, providing regulatory guidance and expansion of the product range, including dosage form possibilities. Moreover, it should enable the use of diverse good manufacturing practice (GMP)-ready 3D printing techniques for the production of various drug products for the pediatric patient population.
Luminescent Coatings Based on (3-Aminopropyl)triethoxysilane and Europium Complex β-Diketophosphazene
Authors: Maslennikova Violetta V. , Filatov Sergey N. , Orlov Alexey V. , Surin Nikolay M. , Svidchenko Evgeniya A. , Chistyakov Evgeniy M.
Published: February 2022

The reaction of β-diketophosphazene with the europium (III) salt synthesized the corresponding metal complex which was structured with (3-aminopropyl)triethoxysilane and treated with dibenzoylmethane for additional coordination of europium atoms. The polymer thus obtained exhibits luminescence with a maximum of 615 nm, which is characteristic of europium. The polymer is thermally stable up to 300 °C, the coating based on it has a contact angle of 101°, and the adhesive strength of the coating to non-finished glass (according to ISO 2409: 2013) is 1 point.
Characterization of Sodium Alginate—Locust Bean Gum Films Reinforced with Daphnetin Emulsions for the Development of Active Packaging
Authors: Cheng Hao , Cao Jie , Liu Wenru , Mei Jun , Xie Jing
Published: February 2022

In this study, we characterized an active film made of sodium alginate (SA)—locust bean gum (LBG) containing daphnetin-based film. Physicochemical characteristics, as well as antioxidant and antibacterial properties, were investigated. The results showed that the addition of a low concentration of daphnetin increased the flexibility of SA–LBG cling film, leading to an improvement in elongation at break and tensile strength. As the daphnetin content increased, solubility, brightness and transparency of the cling film decreased, and the moisture permeability increased. The antioxidant capacity and antibacterial activity of films with daphnetin were improved compared to those of the basal film. In addition, the cling film formed by adsorption had higher bacterial (Shewanella putrefaciens and Pseudomonas fluorescens) inhibition and antioxidant activity rates than direct film formation. The results indicate that the combination of daphnetin in SA–LBG film provides an active film with antioxidant and antibacterial properties, with potential for the development of food-grade packaging material.
Antimicrobial Activity of Cellulose Based Materials
Authors: Nemeş Nicoleta Sorina , Ardean Cristina , Davidescu Corneliu Mircea , Negrea Adina , Ciopec Mihaela , Duţeanu Narcis , Negrea Petru , Paul Cristina , Duda-Seiman Daniel , Muntean Delia
Published: February 2022

Biomaterials available for a wide range of applications are generally polysaccharides. They may have inherent antimicrobial activity in the case of chitosan. However, in order to have specific functionalities, bioactive compounds must be immobilized or incorporated into the polymer matrix, as in the case of cellulose. We studied materials obtained by functionalizing cellulose with quaternary ammonium salts: dodecyl-trimethyl-ammonium bromide (DDTMABr), tetradecyl-trimethyl-ammonium bromide (TDTMABr), hexadecyl-trimethyl ammonium chloride (HDTMACl), some phosphonium salts: dodecyl-triphenyl phosphonium bromide (DDTPPBr) and tri n-butyl-hexadecyl phosphonium bromide (HDTBPBr) and extractants containing sulphur: 2-mercaptobenzothiazole (MBT) and thiourea (THIO). Cel-TDTMABr material, whose alkyl substituent chain conformation was shortest, showed the best antimicrobial activity for which, even at the lowest functionalization ratio, 1:0.012 (w:w), the microbial inhibition rate is 100% for Staphylococcus aureus, Escherichia coli, and Candida albicans. Among the materials obtained by phosphonium salt functionalization, Cel-DDTPPBr showed a significant bactericidal effect compared to Cel-HDTBPBr. For instance, to the same functionalization ratio = 1:0.1, the inhibition microbial growth rate is maximum in the case of Cel-DDTPPBr for Staphylococcus aureus, Escherichia coli, and Candida albicans. At the same time, for the Cel-HDTBPBr material, the total bactericidal effect is not reached even at the functionalization ratio 1:0.5. This behavior is based on the hydrophobicity difference between the two extractants, DDTPPBr and HDTBPBr. Cel-MBT material has a maximum antimicrobial effect upon Staphylococcus aureus, Escherichia coli, and Candida albicans at functionalized ratio = 1:0.5. Cel-THIO material showed a bacteriostatic and fungistatic effect, the inhibition of microbial growth being a maximum of 76% for Staphylococcus aureus at the functionalized ratio = 1:0.5. From this perspective, biomaterials obtained by SIR impregnation of cellulose can be considered a benefit to be used to obtain biomass-derived materials having superior antimicrobial properties versus the non-functional support.
Investigation of the Compatibility and Damping Performance of Graphene Oxide Grafted Antioxidant/Nitrile-Butadiene Rubber Composite: Insights from Experiment and Molecular Simulation
Authors: Song Meng , Yue Xiulin , Chang Chaokang , Cao Fengyi , Yu Guomin , Wang Xiujuan
Published: February 2022

Rubber damping materials are widely used in electronics, electrical and other fields because of their unique viscoelasticity. How to prepare high-damping materials and prevent small molecule migration has attracted much attention. Antioxidant 4010NA was successfully grafted onto graphene oxide (GO) to prepare an anti-migration antioxidant (GO-4010NA). A combined molecular dynamics (MD) simulation and experimental study is presented to investigate the effects of small molecules 4010NA, GO, and GO-4010NA on the compatibility and damping properties of nitrile-butadiene rubber (NBR) composites. Differential scanning calorimetry (DSC) results showed that both 4010NA and GO-4010NA had good compatibility with the NBR matrix, and the Tg of GO-4010NA/NBR composite was improved. Dynamic mechanical analysis (DMA) data showed that the addition of GO-4010NA increased the damping performance of NBR than that of the addition of 4010NA. Molecular dynamics (MD) simulation results show GO-4010NA/NBR composites have the smallest free volume fraction (FFV) and the largest binding energy. GO-4010NA has a strong interaction with NBR due to the forming of hydrogen bonds (H-bonds). Grafting 4010NA onto GO not only inhibits the migration of 4010NA but also improves the damping property of NBR matrixes. This study provides new insights into GO grafted small molecules and the design of high-damping composites.
In Situ Construction of Thermotropic Shape Memory Polymer in Wood for Enhancing Its Dimensional Stability
Authors: Zhang Wenhao , Zhou Jianchao , Cao Zhijin , Wu Xinxing , Wang Hui , Han Shuaibo , Zhang Yan , Sun Fangli , Zhang Ting
Published: February 2022

The extension of wood to a wider field has been restrained significantly due to its dimensional instability that arises from variation in moisture content, which in turn brings about the risk of cracking, warping or distortion. This work proposed a novel strategy to stabilize wood by means of the in situ construction of a thermotropic shape memory polymer (SMP) inside wood. The cross-linked copolymer network (PMP) with good shape memory behavior was first investigated based on the reaction of methyl methacrylate (MMA) and polyethylene glycol diacrylate (PEGDA) in a water/ethanol solution; then, the PMP was constructed inside wood via vacuum-pressure impregnation and in situ polymerization. The weight gain, volume increment and morphology observations clearly revealed that the PMP was mainly present in wood cell lumens, cell walls and pits. The presence of PMP significantly enhanced the dimensional stability of and reduced the cracks in wood. The desirable shape recovery abilities of PMP under heating-cooling cycles were considered to be the main reasons for wood dimensional stabilization, because it could counteract the internal stress or retard the shrinkage of cell walls once water was evaporated from the wood. This study provided a novel and reliable approach for wood modification.
Numerical Simulation of Microwave Ablation in the Human Liver
Authors: Gorman John , Tan Winston , Abraham John
Published: February 2022

Microwave thermal ablation was developed as an alternative to other forms of thermal ablation procedures. The objective of this study is to numerically model a microwave ablation probe operating at the 2.45 GHz level using the finite element and finite volume methods to provide a comprehensive and repeatable study within a human male approximately 25 to 30 years old. The three-dimensional physical model included a human liver along with the surrounding tissues and bones. Three different input powers (10, 20, and 30 watts) were studied, along with the effect of the probe’s internal coolant flow rate. One of the primary results from the numerical simulations was the extent of affected tissue from the microwave probe. The resulting time and temperature results were used to predict tissue damage using an injury integral method. The numerical approach was validated with available experimental data and was found to be within 6% of the average experimentally measured temperatures.
TLSCA-SVM Fault Diagnosis Optimization Method Based on Transfer Learning
Authors: Zhang Aihua , Yu Danlu , Zhang Zhiqiang
Published: February 2022

In fault-diagnosis classification, a pressing issue is the lack of target-fault samples. Obtaining fault data requires a great amount of time, energy and financial resources. These factors affect the accuracy of diagnosis. To address this problem, a novel fault-diagnosis-classification optimization method, namely TLSCA-SVM, which combines the sine cosine algorithm and support vector machine (SCA-SVM) with transfer learning, is proposed here. Considering the availability of fault data, this thesis uses the data generated by analog circuits from different faults for analysis. Firstly, the data signal is collected from different faults of the analog circuit, and then the characteristic data are extracted from the data signals by the wavelet packets. Secondly, to employ the principal component analysis (PCA) reduces the feature-value dimension. Lastly, as an auxiliary condition, the error-penalty item is added to the objective function of the SCA-SVM classifier to construct an innovative fault-diagnosis model namely TLSCA-SVM. Among them, the Sallen–Key bandpass filter circuit and the CSTV filter circuit are used to provide the data for horizontal- and vertical-contrast classification results. Comparing the SCA with the five optimization algorithms, it is concluded that the performance of SCA optimization parameters has certain advantages in the classification accuracy and speed. Additionally, to prove the superiority of the SCA-SVM classification algorithm, the five classification algorithms are compared with the SCA-SVM algorithm. Simulation results showed that the SCA-SVM classification has higher precision and a faster response time compared to the others. After adding the error penalty term to SCA-SVM, TLSCA-SVM requires fewer fault samples to process fault diagnosis. Ultimately, the method which is proposed could not only perform fault diagnosis effectively and quickly, but also could run effectively to achieve the effect of transfer learning in the case of less failure data.
A Constant Cascade: Ancient and Medieval Verse on the Four Waterways
Authors: Williams Nicholas Morrow
Published: February 2022

The literary representation of China’s great rivers has repeatedly been transformed by changes in religious belief and ritual. In the Book of Songs, rivers figure primarily as political boundaries and figures of separation. Though they may already play a role in religious rites, their geographical identity is paramount. However, in the “Nine Songs” of the Elegies of Chu, they appear in a new guise as sites of divine encounter and shamanistic flight. Their treatment in later works may be regarded as a peculiar synthesis of these two traditions. Once the Four Waterways were designated as the object of state ritual in the Western Han, their divine status was widely accepted, along with explicitly political ramifications. For instance, the god of the Yellow River was honored as a participant in flood control and imperial governance writ large. Meanwhile, the tradition of the epideictic fu also celebrates the awesome scale of China’s waterways, reaching a culmination not long after the fall of the Han in Guo Pu’s (286–324) “Rhapsody on the Yangzi River”. However, it is noteworthy how often the fu tradition eschews material description of rivers in favor of celebrating their numinous powers and divine inhabitants. Because of this turn towards the divine in the medieval literary tradition, it is no accident that one of the most prominent subjects of fluvial verse in the Tang is not body of water at all but rather the Sky River, or Milky Way.
The Soka Gakkai Practice of Buppō and the Discourse on Religion in Japan
Authors: Fisker-Nielsen Anne Mette
Published: February 2022

This paper investigates the Japanese Nichiren Buddhist organization, Soka Gakkai (SG), whose members have supported the political party known as Kōmeitō, or Clean Government Party, in Japan for over half a century. SG members have often been criticized as ‘impure’ political actors, undergoing frequent public questioning of their motivations for engaging in electoral politics in light of their ‘religious’ status. The paper shows how the SG members’ support for Kōmeitō at a qualitative level indeed transcends the typical demarcations of the ‘secular-religious’ binary system. However, they also simultaneously challenge the term ‘religion’ that has functioned as an ideology in the creation of statecraft and in their competition for legitimacy. The current paper is based on long-term fieldwork, extensive interviews, and doctrinal analyses that highlight how socially productive this discourse on religion has been. It also shows how a counter-episteme, rooted in Nichiren’s theory of the Risshō Ankoku Ron and the idea of kōsen-rufu, sought to bring a ‘Buddha’ consciousness to bear on individual and collective action as a model for alternative ‘politics’. Contrary to many claims, this did not entail contesting the modern institutional separation of ‘church’ and ‘state’, but is rather an attempt to find legitimacy for participating in ‘Japan-making’ in ways that cannot easily be understood or confined to explanations framed within the ‘religious-secular’ binary system.
Musical Epigraphies of Antiphon Salve Regina by Cristóbal de Morales: The Walls of the Sanctuary of Nuestra Señora del Pueyo, Villamayor de Gállego, Zaragoza
Authors: Seguí Montiel
Published: February 2022

In 1990 a publication by Pedro Calahorra reported a unique musical notation of a Salve on the walls of the Sanctuary of Nuestra Señora del Pueyo in Villamayor de Gállego, Zaragoza. The contributions offered in this article have enhanced research in this area through a revised study of this musical epigraphy. The analysis of the palaeography of notation reveals the dating of the work and, therefore, a possible collation with the Spanish polyphonic sources belonging to the white mensural notation, determining that it is the Salve Regina in four by Cristóbal de Morales. This study aims to recognize musical epigraphies as historiographic-musical sources of information capable of intervening in the reconstruction of a musical past, so they must be restored, preserved, catalogued and displayed like any historical document, regardless of their physical support. The Salve Regina written on the walls of the Villamayor de Gállego sanctuary is the witness of a Christian tradition of devotion to the Virgin Mary. Within the Rite of Salve this chant was the most popular in the Iberian Peninsula during the Renaissance.
An Improved Sea Ice Classification Algorithm with Gaofen-3 Dual-Polarization SAR Data Based on Deep Convolutional Neural Networks
Authors: Zhang Jiande , Zhang Wenyi , Hu Yuxin , Chu Qingwei , Liu Lei
Published: February 2022

The distribution of sea ice is one of the major safety hazards for sea navigation. As human activities in polar regions become more frequent, monitoring and forecasting of sea ice are of great significance. In this paper, we use SAR data from the C-band synthetic aperture radar (SAR) Gaofen-3 satellite in the dual-polarization (VV, VH) fine strip II (FSII) mode of operation to study the Arctic sea ice classification in winter. SAR data we use were taken in the western Arctic Ocean from January to February 2020. We classify the sea ice into four categories, namely new ice (NI), thin first-year ice (tI), thick first-year ice (TI), and old ice (OI), by referring to the ice maps provided by the Canadian Ice Service (CIS). Then, we use the deep learning model MobileNetV3 as the backbone network, input samples of different sizes, and combine the backbone network with multiscale feature fusion methods to build a deep learning model called Multiscale MobileNet (MSMN). Dual-polarization SAR data are used to synthesize pseudocolor images and produce samples of sizes 16 × 16 × 3, 32 × 32 × 3, and 64 × 64 × 3 as input. Ultimately, MSMN can reach over 95% classification accuracy on testing SAR sea ice images. The classification results using only VV polarization or VH polarization data are tested, and it is found that using dual-polarization data could improve the classification accuracy by 10.05% and 9.35%, respectively. When other classification models are trained using the training data from this paper for comparison, the accuracy of MSMN is 4.86% and 1.84% higher on average than that of the model built using convolutional neural networks (CNNs) and ResNet18 model, respectively.
Identification and Correlation Analysis of Engineering Environmental Risk Factors along the Qinghai–Tibet Engineering Corridor
Authors: Zhang Tianqi , Yu Wenbing , Lu Yan , Chen Lin
Published: February 2022

Global warming has increased the security risk of permafrost environment in the Tibetan Plateau, which has been threatening infrastructures along the Qinghai–Tibet Engineering Corridor (QTEC). Combined with the traditional risk identification and the causal feedback relationship of system dynamics, the authors present a novel engineering environment risk identification model including five risk subsystems, i.e., regional geomorphology, climate change, ecological environment, permafrost environment and water environment. Our model could successfully identify the interaction relationships and transmission path among risk factors of the environment of the QTEC. The basic data calculation, interaction degree analysis and regional distribution characteristic analysis of the identified risk factors were carried out by using a geographic information system (GIS), a partial correlation analysis and a zoning analysis. The results show that the static factors (i.e., elevation, slope, aspect, relief degree of land surface and volume ice content) mainly affected the spatial distribution of environmental risk factors, while the climate change factors (i.e., mean annual air temperature, mean annual precipitation and surface solar radiation), among the dynamic factors, were the root factors of the dynamic changes in environmental risks. The model identified five types of parallel risk paths in the QTEC. This novel method and proposed model can be used to identify and assess multi-scale engineering environmental risks in the cryosphere.
Digital Terrain Modelling by Remotely Piloted Aircraft: Optimization and Geometric Uncertainties in Precision Coffee Growing Projects
Authors: Santana Lucas Santos , Ferraz Gabriel Araújo e Silva , Marin Diego Bedin , Faria Rafael de Oliveira , Santana Mozarte Santos , Rossi Giuseppe , Palchetti Enrico
Published: February 2022

The implantation of coffee crop plantations requires cartographic data for dimensioning areas and planning the planting line. Digital terrain models (DTMs) obtained from remotely piloted aircraft (RPA) can contribute to efficient data collection for topography making this technique applicable to precision coffee projects. Aiming to achieve efficiency in the collection, processing and photogrammetric products quality, flight configurations and image processing were evaluated. Two hundred sixty-five points obtained by Global Navigation Satellite System (GNSS) receivers characterized the topographic surface. Then eighteen flight missions were carried out by RPA in the configurations of altitude above ground level (AGL) and frontal and lateral image overlay. In addition, different point cloud formats evaluated the image processing (time) efficiency in DTM. Flights performed at 120 m AGL and 80 × 80% overlap showed higher assertiveness and efficiency in generation DTMs. The 90 m AGL flight showed great terrain detail, causing significant surface differences concerning the topography obtained by GNSS. An increase in image overlap requires longer processing times, not contributing linearly to the geometric quality of orthomosaic. Slope ranges up to 20% are considered reliable for precision coffee growing projects; above 20% overestimates the slope values of the land. Changes in flight settings and image processing are satisfactory for precision coffee projects. Image overlap reduction was significant in reducing the processing time without influencing the quality of the DTMs. In addition, image processing performed in shallow point clouds did not interfere with the DTMs quality.
Accurate Identification of Pine Wood Nematode Disease with a Deep Convolution Neural Network
Authors: Huang Jixia , Lu Xiao , Chen Liyuan , Sun Hong , Wang Shaohua , Fang Guofei
Published: February 2022

Pine wood nematode disease is a devastating pine disease that poses a great threat to forest ecosystems. The use of remote sensing methods can achieve macroscopic and dynamic detection of this disease; however, the efficiency and accuracy of traditional remote sensing image recognition methods are not always sufficient for disease detection. Deep convolutional neural networks (D-CNNs), a technology that has emerged in recent years, have an excellent ability to learn massive, high-dimensional image features and have been widely studied and applied in classification, recognition, and detection tasks involving remote sensing images. This paper uses Gaofen-1 (GF-1) and Gaofen-2 (GF-2) remote sensing images of areas with pine wood nematode disease to construct a D-CNN sample dataset, and we train five popular models (AlexNet, GoogLeNet, SqueezeNet, ResNet-18, and VGG16) through transfer learning. Finally, we use the “macroarchitecture combined with micromodules for joint tuning and improvement” strategy to improve the model structure. The results show that the transfer learning effect of SqueezeNet on the sample dataset is better than that of other popular models and that a batch size of 64 and a learning rate of 1 × 10−4 are suitable for SqueezeNet’s transfer learning on the sample dataset. The improvement of SqueezeNet’s fire module structure by referring to the Slim module structure can effectively improve the recognition efficiency of the model, and the accuracy can reach 94.90%. The final improved model can help users accurately and efficiently conduct remote sensing monitoring of pine wood nematode disease.
Dynamic Expansion of Urban Land in China’s Coastal Zone since 2000
Authors: Du Peipei , Hou Xiyong , Xu He
Published: February 2022

Although a major region with strong urbanization, there is not yet a systematic and comprehensive understanding of urban expansion during the last 20 years for China’s coastal zone. In this paper, based on remote sensing techniques, and using indicators such as new urban land proportion, annual urban increase, and annual growth rate, as well as a landscape expansion index reflecting the urban expansion type (e.g., edge-expansion, infilling, and outlying), we measured the dynamic expansion of urban land in China’s coastal zone since 2000. The results indicated that: (1) China’s coastal zone experienced rapid urbanization from 2000 to 2020, with the new urban land and annual urban growth rate at 17,979.72 km2 and 4.83%, respectively. The new urban land was mainly concentrated in economically advanced regions, such as Bohai Rim, Shandong Peninsula, the Yangtze River delta, and the Pearl River delta. (2) The urban growth rates of coastal cities in Liaoning, Hebei, Shandong, southeast Fujian, and Taiwan became slower over time, with a sharp decline during 2015–2020. In the mid and south of China’s coastal zone, such as coastal cities in Jiangsu, Guangxi, and Hainan, there was slow urbanization before 2015, and urban land expanded dramatically during 2015–2020. (3) The urban expansion of China’s coastal zone was dominated by edge-expansion after 2000, but it went through a low-speed and intensive development stage during 2010–2015, with an increase in urban land less than 50% of that in the other three five-year periods, and the most significant filling of urban space compared with the other three five-year periods, which was probably caused by the global financial crisis. (4) The spatial-temporal differences in the urbanization process in China’s coastal zone were largely consequent on national economic development strategies and regional development plans implemented in China’s coastal zone.
Long-Term Impacts of COVID-19 Lockdown on the NO2 Concentrations and Urban Thermal Environment: Evidence from the Five Largest Urban Agglomerations in China
Authors: Zhang Ninghui , Ye Haipeng , Zheng Ji , Leng Xuejing , Meng Dan , Li Yu
Published: February 2022

Under the threat of COVID-19, many regions around the world implemented lockdown policies to control the spread of the virus. This restriction on both social and economic activities has improved the quality of the environment in certain aspects. However, most previous studies have only focused on the short-term impact of lockdown policies on the urban environment. The long-term effects of lockdown require a more focused exploration and analysis. Thus, five major urban agglomerations in China were selected as the research area; changes in the numerical and spatial distribution of NO2 concentration and surface temperature during four different lockdown stages in 2019, 2020, and 2021 were investigated to analyze the long-term effects of lockdown policies on the urban environment. The results indicated that the impact of shorter lockdowns was short-term and unsustainable; the NO2 concentrations increased again with the resumption of production. Compared with air pollutants, thermal environmental problems are more complex. The effect of the lockdown policy was not reflected in the decrease in the area proportions of the high- and sub-high-temperature regions but rather in the spatial distribution of the high-temperature area, which was manifested as a fragmentation and dispersion of heat source patches. In addition to the severity of the lockdown, the impact of the lockdown policy was also closely related to the level of development and industrial structure of each city. Among the urban environments of the five agglomerations, the most affected were the Yangtze River Delta and Yangtze River Middle-Reach urban agglomerations, which had the largest decline in NO2 concentrations and the most notable fragmentation of heat source patches.
SmartWater: A Service-Oriented and Sensor Cloud-Based Framework for Smart Monitoring of Water Environments
Authors: Mezni Haithem , Driss Maha , Boulila Wadii , Ben Atitallah Safa , Sellami Mokhtar , Alharbi Nouf
Published: February 2022

Due to the sharp increase in global industrial production, as well as the over-exploitation of land and sea resources, the quality of drinking water has deteriorated considerably. Furthermore, nowadays, many water supply systems serving growing human populations suffer from shortages since many rivers, lakes, and aquifers are drying up because of global climate change. To cope with these serious threats, smart water management systems are in great demand to ensure vigorous control of the quality and quantity of drinking water. Indeed, water monitoring is essential today since it allows to ensure the real-time control of water quality indicators and the appropriate management of resources in cities to provide an adequate water supply to citizens. In this context, a novel IoT-based framework is proposed to support smart water monitoring and management. The proposed framework, named SmartWater, combines cutting-edge technologies in the field of sensor clouds, deep learning, knowledge reasoning, and data processing and analytics. First, knowledge graphs are exploited to model the water network in a semantic and multi-relational manner. Then, incremental network embedding is performed to learn rich representations of water entities, in particular the affected water zones. Finally, a decision mechanism is defined to generate a water management plan depending on the water zones’ current states. A real-world dataset has been used in this study to experimentally validate the major features of the proposed smart water monitoring framework.
GRACE Data Explore Moho Change Characteristics Beneath the South America Continent near the Chile Triple Junction
Authors: Sun Pengchao , Guo Changsheng , Wei Dongping
Published: February 2022

The internal and external mass migration and redistribution of the Earth system are usually accompanied by changes in the gravity field, and the Gravity Recovery and Climate Experiment (GRACE) has been proven to be able to effectively monitor and evaluate such changes. The Chile Triple Junction (CTJ) is the convergence point of the Nazca plate, the Antarctic plate and the South American plate. Subductions of different forms and rates in the north and south of the CTJ have varying degrees of impact on the surface and underground material changes of the South American plate. In this study, GRACE data are used in the estimation of the comprehensive mass changes in the South America Continent (SAC) Near the CTJ (~15° range). In addition, surface movement changes constrained by GNSS data cannot fully explain the GRACE results after deducting hydrological information, which indicates that residual signals might be attributed to mass changes beneath the crust, that is, the Moho interface deformation. After eliminating surface movement and hydrological signals from the comprehensive mass changes of GRACE, this study obtains the deep structural information and calculates the Moho changes of three significant regions with rates of −2.12 ± 0.67 cm/yr, 0.18 ± 0.19 cm/yr and −6.46 ± 1.31 cm/yr, respectively. Results have demonstrated that the subductions of the Nazca plate and the Antarctica plate have an effect on the uneven deformation of the Moho interface beneath the SAC. The Moho beneath the SAC mainly shows a deepening trend, but it is uplifted in some areas north of CTJ. On the whole, the rate of Moho changes is greater in the south than in the north. The relationship between Moho changes and surface changes also indicates that a longer timescale may be needed for maintaining isostatic balance.
Super-Resolution Network for Remote Sensing Images via Preclassification and Deep–Shallow Features Fusion
Authors: Yue Xiuchao , Chen Xiaoxuan , Zhang Wanxu , Ma Hang , Wang Lin , Zhang Jiayang , Wang Mengwei , Jiang Bo
Published: February 2022

A novel super-resolution (SR) method is proposed in this paper to reconstruct high-resolution (HR) remote sensing images. Different scenes of remote sensing images have great disparities in structural complexity. Nevertheless, most existing SR methods ignore these differences, which increases the difficulty to train an SR network. Therefore, we first propose a preclassification strategy and adopt different SR networks to process the remote sensing images with different structural complexity. Furthermore, the main edge of low-resolution images are extracted as the shallow features and fused with the deep features extracted by the network to solve the blurry edge problem in remote sensing images. Finally, an edge loss function and a cycle consistent loss function are added to guide the training process to keep the edge details and main structures in a reconstructed image. A large number of comparative experiments on two typical remote sensing images datasets (WHURS and AID) illustrate that our approach achieves better performance than state-of-the-art approaches in both quantitative indicators and visual qualities. The peak signal-to-noise ratio (PSNR) value and the structural similarity (SSIM) value using the proposed method are improved by 0.5353 dB and 0.0262, respectively, over the average values of five typical deep learning methods on the ×4 AID testing set. Our method obtains satisfactory reconstructed images for the subsequent applications based on HR remote sensing images.
Automatic and Accurate Extraction of Sea Ice in the Turbid Waters of the Yellow River Estuary Based on Image Spectral and Spatial Information
Authors: Qiu Huachang , Gong Zhaoning , Mou Kuinan , Hu Jianfang , Ke Yinghai , Zhou Demin
Published: February 2022

Sea ice is an important part of the global cryosphere and an important variable in the global climate system. Sea ice also presents one of the major natural disasters in the world. The automatic and accurate extraction of sea ice extent is of great significance for the study of climate change and disaster prevention. The accuracy of sea ice extraction in the Yellow River Estuary is low due to the large dynamic changes in the suspended particulate matter (SPM). In this study, a set of sea ice automatic extraction method systems combining image spectral information and textural information is developed. First, a sea ice spectral information index that can adapt to sea areas with different turbidity levels is developed to mine the spectral information of different types of sea ice. In addition, the image’s textural feature parameters and edge point density map are extracted to mine the spatial information concerning the sea ice. Then, multi-scale segmentation is performed on the image. Finally, the OTSU algorithm is used to determine the threshold to achieve automatic sea ice extraction. The method was successfully applied to Gaofen-1 (GF1), Sentinel-2, and Landsat 8 images, where the extraction accuracy of sea ice was over 93%, which was more than 5% higher than that of SVM and K-Means. At the same time, the method was applied to the Liaodong Bay area, and the extraction accuracy reached 99%. These findings reveal that the method exhibits good reliability and robustness.
Can GPM IMERG Capture Extreme Precipitation in North China Plain?
Authors: Zhang Dasheng , Yang Mingxiang , Ma Meihong , Tang Guoqiang , Wang Tsechun , Zhao Xun , Ma Suying , Wu Jin , Wang Wei
Published: February 2022

Extreme precipitation events (EPE) often cause catastrophic floods accompanied by serious economic losses and casualties. The latest version (V06) of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) provides global satellite precipitation data from 2000 at a higher spatiotemporal resolution with improved quality. It is scientifically and practically important to assess the accuracy of the IMERG V06 in capturing extreme precipitation. This study evaluates the two widely used products of IMERG during 2000–2018, i.e., IMERG late run (IMERG-L) and IMERG final run (IMERG-F), in the densely populated and flood-prone North China Plain. The accuracy of the IMERG V06 is evaluated with ground measurements from rain gauge stations at multiple scales (hourly, daily, and seasonally). A novel target tracking method is introduced to extract three-dimensional (3D) extreme precipitation events, and the near-real-time uncalibrated PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System) and GSMAP (Global Satellite Mapping of Precipitation) satellite data are added to further evaluate IMERG’s performance during extreme precipitation. Finally, for flash flood events induced by extreme rainfall in the Hebei Province from 15 to 23 July 2016, the accuracy of capturing the event with IMERG-F and IMERG-L was verified. Results reveal that IMERG-F is better than IMERG-L at all investigated scales (hourly, daily, and seasonally), but the difference between the two products is less at higher time resolutions. Both products manifest decreased performance when capturing 3D extreme precipitation events, and comparatively, IMERG-F performs better than IMERG-L. IMERG-F exhibits a distinct discontinuity in extreme precipitation thresholds between land and ocean, which is a limitation of IMERG-F not documented in previous studies. Moreover, IMERG-L and IMERG-F are comparable at an hourly scale for some metrics, which is beyond the expectation that IMERG-F is notably better than IMERG-L. This study provides a scientific basis for the performance of satellite precipitation products and contributes to guiding users when applying global precipitation products.
Impacts of Drought and Climatic Factors on Vegetation Dynamics in the Yellow River Basin and Yangtze River Basin, China
Authors: Jiang Weixia , Niu Zigeng , Wang Lunche , Yao Rui , Gui Xuan , Xiang Feifei , Ji Yuxi
Published: February 2022

Understanding the impacts of drought and climate change on vegetation dynamics is of great significance in terms of formulating vegetation management strategies and predicting future vegetation growth. In this study, Pearson correlation analysis was used to investigate the correlations between drought, climatic factors and vegetation conditions, and linear regression analysis was adopted to investigate the time-lag and time-accumulation effects of climatic factors on vegetation coverage based on the standardized evapotranspiration deficit index (SEDI), normalized difference vegetation index (NDVI), and gridded meteorological dataset in the Yellow River Basin (YLRB) and Yangtze River Basin (YTRB), China. The results showed that (1) the SEDI in the YLRB showed no significant change over time and space during the growing season from 1982 to 2015, whereas it increased significantly in the YTRB (slope = 0.013/year, p < 0.01), and more than 40% of the area showed a significant trend of wetness. The NDVI of the two basins, YLRB and YTRB, increased significantly at rate of 0.011/decade and 0.016/decade, respectively (p < 0.01). (2) Drought had a significant impact on vegetation in 49% of the YLRB area, which was mainly located in the northern region. In the YTRB, the area significantly affected by drought accounted for 21% of the total area, which was mainly distributed in the Sichuan Basin. (3) In the YLRB, both temperature and precipitation generally had a one-month accumulated effect on vegetation conditions, while in the YTRB, temperature was the major factor leading to changes in vegetation. In most of the area of the YTRB, the effect of temperature on vegetation was also a one-month accumulated effect, but there was no time effect in the Sichuan Basin. Considering the time effects, the contribution of climatic factors to vegetation change in the YLRB and YTRB was 76.7% and 63.2%, respectively. The explanatory power of different vegetation types in the two basins both increased by 2% to 6%. The time-accumulation effect of climatic factors had a stronger explanatory power for vegetation growth than the time-lag effect.