bluuebunny/crossref_metadata_2025 huggingface dataset:
Pyrazole-Curcumin Suppresses Cardiomyocyte Hypertrophy by Disrupting the CDK9/CyclinT1 Complex
Authors: Funamoto Masafumi , Sunagawa Yoichi , Gempei Mai , Shimizu Kana , Katanasaka Yasufumi , Shimizu Satoshi , Hamabe-Horiike Toshihide , Appendino Giovanni , Minassi Alberto , Koeberle Andreas , Komiyama Maki , Mori Kiyoshi , Hasegawa Koji , Morimoto Tatsuya
Published: June 2022

The intrinsic histone acetyltransferase (HAT), p300, has an important role in the development and progression of heart failure. Curcumin (CUR), a natural p300-specific HAT inhibitor, suppresses hypertrophic responses and prevents deterioration of left-ventricular systolic function in heart-failure models. However, few structure–activity relationship studies on cardiomyocyte hypertrophy using CUR have been conducted. To evaluate if prenylated pyrazolo curcumin (PPC) and curcumin pyrazole (PyrC) can suppress cardiomyocyte hypertrophy, cultured cardiomyocytes were treated with CUR, PPC, or PyrC and then stimulated with phenylephrine (PE). PE-induced cardiomyocyte hypertrophy was inhibited by PyrC but not PPC at a lower concentration than CUR. Western blotting showed that PyrC suppressed PE-induced histone acetylation. However, an in vitro HAT assay showed that PyrC did not directly inhibit p300-HAT activity. As Cdk9 phosphorylates both RNA polymerase II and p300 and increases p300-HAT activity, the effects of CUR and PyrC on the kinase activity of Cdk9 were examined. Phosphorylation of p300 by Cdk9 was suppressed by PyrC. Immunoprecipitation-WB showed that PyrC inhibits Cdk9 binding to CyclinT1 in cultured cardiomyocytes. PyrC may prevent cardiomyocyte hypertrophic responses by indirectly suppressing both p300-HAT activity and RNA polymerase II transcription elongation activity via inhibition of Cdk9 kinase activity.
Integrating Inflammation-Responsive Prodrug with Electrospun Nanofibers for Anti-Inflammation Application
Authors: Ye Jingjing , Gong Min , Song Jian , Chen Shu , Meng Qinghan , Shi Rui , Zhang Liqun , Xue Jiajia
Published: June 2022

Chronic inflammation plays a side effect on tissue regeneration, greatly inhibiting the repair or regeneration of tissues. Conventional local delivery of anti-inflammation drugs through physical encapsulation into carriers face the challenges of uncontrolled release. The construction of an inflammation-responsive prodrug to release anti-inflammation drugs depending on the occurrence of inflammation to regulate chronic inflammation is of high need. Here, we construct nanofiber-based scaffolds to regulate the inflammation response of chronic inflammation during tissue regeneration. An inflammation-sensitive prodrug is synthesized by free radical polymerization of the indomethacin-containing precursor, which is prepared by the esterification of N-(2-hydroxyethyl) acrylamide with the anti-inflammation drug indomethacin. Then, anti-inflammation scaffolds are constructed by loading the prodrug in poly(ε-caprolactone)/gelatin electrospun nanofibers. Cholesterol esterase, mimicking the inflammation environment, is adopted to catalyze the hydrolysis of the ester bonds, both in the prodrug and the nanofibers matrix, leading to the generation of indomethacin and the subsequent release to the surrounding. In contrast, only a minor amount of the drug is released from the scaffold, just based on the mechanism of hydrolysis in the absence of cholesterol esterase. Furthermore, the inflammation-responsive nanofiber scaffold can effectively inhibit the cytokines secreted from RAW264.7 macrophage cells induced by lipopolysaccharide in vitro studies, highlighting the great potential of these electrospun nanofiber scaffolds to be applied for regulating the chronic inflammation in tissue regeneration.
UV-Vis Spectrophotometer as an Alternative Technique for the Determination of Hydroquinone in Vinyl Acetate Monomer
Authors: Rashid Md Al Mamunur , Rahman Mofizur , Mahmud ASM Obaidullah , Morshed Ali Shazzad Mohammad , Haque Md Masudul , Hossain Md Mobarak
Published: June 2022

As an appropriate quantity of hydroquinone (HQ) is essential to safeguard inhibition characteristics by eliminating the risk of self-polymerization of vinyl acetate monomer (VAM), the determination of the HQ content in VAM is very crucial to ensure the stability of VAM during storage and transportation as well as to achieve the possibility of a proper polymerization reaction. In this study, a simple, cheap, time-saving, and easy method has been developed by which the HQ content in VAM can be measured quickly based on the measurement of UV-Vis absorbance of the HQ content at 293 nm using methanol as a blank. No color development is required for this determination process, and the HQ content in the VAM can be measured directly without any further processing. The limit of detection, limit of quantification, linearity range, accuracy, precision, robustness, and measurement uncertainty of this method have been measured and analyzed and found to be within the acceptable limit and range. The method shows linearity within 0.36–25.0 ppm HQ content in the solution range with a regression coefficient of 0.9999, a relative spike recovery of 101.35%, precision of 1.36%, relative bias of 0.55%, and robustness with a temperature variation of −5 °C.
Genomic Survey of PEBP Gene Family in Rice: Identification, Phylogenetic Analysis, and Expression Profiles in Organs and under Abiotic Stresses
Authors: Zhao Chunyu , Zhu Mo , Guo Yanying , Sun Jian , Ma Wenhong , Wang Xiaoxue
Published: June 2022

Phosphatidylethanolamine-binding-protein (PEBP) domain-containing proteins play important roles in multiple developmental processes of plants; however, functions of few members in the PEBP gene family have been elucidated in rice and other crops. In this study, we found that twenty OsPEBPs genes identified in rice are not evenly distributed on the chromosomes. Four colinear pairs are identified, suggesting the duplication of OsPEBPs during evolution. The OsPEBPs are classified into six subgroups by phylogenetic analysis. The structure of all the OsPEBP genes and encoded proteins are similar. The 262 PEBP domain-containing proteins from crops are divided into six groups. The number of colinear pairs varies between rice and other crops. More than thirty cis-acting elements in the promoter region of OsPEBPs are discovered. Expression profiles of OsPEBP genes are differential. Most of the OsPEBPs expression can be regulated by NaCl, ABA, JA, and light, indicating that OsPEBPs may be involved in the control of the response to the environmental signals. These results lay sound foundation to further explore their functions in development of rice and crops.
Myrtle-Functionalized Nanofibers Modulate Vaginal Cell Population Behavior While Counteracting Microbial Proliferation
Authors: Bellu Emanuela , Diaz Nicia , Kralovič Martin , Divin Radek , Sarais Giorgia , Fadda Angela , Satta Rosanna , Montesu Maria Antonia , Medici Serenella , Brunetti Antonio , Barcessat Ana Rita Pinheiro , Jarošíková Taťána , Rulc Jiří , Amler Evzen , Margarita Valentina , Rappelli Paola , Maioli Margherita
Published: June 2022

Vaginal infections affect millions of women annually worldwide. Therapeutic options are limited, moreover drug-resistance increases the need to find novel antimicrobials for health promotion. Recently phytochemicals were re-discovered for medical treatment. Myrtle (Myrtus communis L.) plant extracts showed in vitro antioxidant, antiseptic and anti-inflammatory properties thanks to their bioactive compounds. The aim of the present study was to create novel nanodevices to deliver three natural extracts from leaves, seeds and fruit of myrtle, in vaginal milieu. We explored their effect on human cells (HeLa, Human Foreskin Fibroblast-1 line, and stem cells isolated from skin), resident microflora (Lactobacillus acidophilus) and on several vaginal pathogens (Trichomonas vaginalis, Escherichia coli, Staphylococcus aureus, Candida albicans, Candida kefyr, Candida glabrata, Candida parapsilosis, Candida krusei). Polycaprolactone-Gelatin nanofibers encapsulated with leaves extract and soaked with seed extracts exhibited a different capability in regard to counteracting microbial proliferation. Moreover, these nanodevices do not affect human cells and resident microflora viability. Results reveal that some of the tested nanofibers are interesting candidates for future vaginal infection treatments.
Alkali-Grafting Proton Exchange Membranes Based on Co-Grafting of α-Methylstyrene and Acrylonitrile into PVDF
Authors: Li Shufeng , Li Xuelin , Fu Pengfei , Zhang Yao
Published: June 2022

A novel alkali-induced grafting polymerization was designed to synthesize a PFGPA proton exchange membrane based on the co-grafting of α-methyl styrene (AMS) and acrylonitrile (AN) into the poly(vinylidenedifluoride) (PVDF) membrane. Three kinds of alkali treatments were used: by immersing the PVDF membranes into a 1 M NaOH solution and mixing the PVDF powders with 16% or 20% Na4SiO4. Then, AMS with AN could be co-grafted into the PVDF backbones in two grafting solvents, THF or IPA/water. Finally, the grafted membranes were sulfonated to provide the PFGPA membranes. In the experiments, the Na4SiO4 treatments showed a greater grafting degree than the NaOH treatment. The grafting degree increased with the increasing amount of Na4SiO4. The grafting solvent also influenced the grafting degree. A 40–50 percent grafting degree was obtained in either the THF or IPA/water solvent after the Na4SiO4 treatment and the THF resulted in a greater grafting degree. FTIR and XPS testified that the PFGPA membranes had been prepared and a partial hydrolysis of the cyano group from AN occurred. The PFGPA membranes with the grafting degree of about 40–50 percent showed a better dimensional stability in methanol, greater water uptake capabilities, and lower ion exchange capacities and conductivities than the Nafion 117 membranes. The PFGPA membrane with the 16% Na4SiO4 treatment and THF as the grafting solvent exhibited a better chemical stability. The obtained experimental results will provide a guide for the synthesis of alkali-grafted PFGPA membranes in practical use.
Refractive Index and Temperature Sensing Performance of Microfiber Modified by UV Glue Distributed Nanoparticles
Authors: Dang Hongtao , Zhang Yan , Qiao Yukun , Li Jin
Published: June 2022

Dielectric materials with high refractive index have been widely studied to develop novel photonic devices for modulating optical signals. In this paper, the microfibers were modified by silicon nanoparticles (NPs) and silver NPs mixed in UV glue with ultra-low refractive index, respectively, whose corresponding optical and sensing properties have been studied and compared. The influence from either the morphological parameters of microfiber or the concentration of NPs on the refractive index sensing performance of microfiber has been investigated. The refractive index sensitivities for the microfiber tapers elaborated with silver NPs and silicon NPs were experimentally demonstrated to be 1382.3 nm/RIU and 1769.7 nm/RIU, respectively. Furthermore, the proposed microfiber was encapsulated in one cut of capillary to develop a miniature temperature probe, whose sensitivity was determined as 2.08 nm/°C, ranging from 28 °C to 43 °C.
Control of Stimuli Sensitivity in pH-Switchable LCST/UCST-Type Thermosensitive Dendrimers by Changing the Dendrimer Structure
Authors: Kojima Chie , Fu Yunshen , Tamaki Mamiko
Published: June 2022

Stimuli-sensitive materials, such as pH- and temperature-responsive polymers, are useful as smart materials. Phenylalanine (Phe)-modified polyamidoamine (PAMAM) dendrimers with succinic acid termini, PAMAM-Phe-Suc, have been reported as unique pH-switchable lower critical solution temperature (LCST)-/upper critical solution temperature (UCST)-type thermosensitive polymers. Regulating the phase transition behavior of dendrimers is important for their applications. This study investigated the relationship between the dendrimer structure and stimuli sensitivity. Phe-modified PAMAM dendrimers with cyclohexanedicarboxylate termini (PAMAM-Phe-CHex) and sulfonate termini (PAMAM-Phe-SO3Na) were synthesized. The temperature-dependent transmittance of these aqueous dendrimer solutions was examined at various pH values. PAMAM-Phe-CHex with Phe at all termini (PAMAM-Phe64-CHex) demonstrated a broad UCST-like phase transition at pH 7.0 but lacked an LCST-type phase transition. PAMAM-Phe-CHex with ≤ 27 Phe residues showed both LCST- and UCST-like phase transitions at different pH values, but the phase transition was broad. PAMAM-Phe-SO3Na showed both LCST- and UCST-type phase transitions at different pH values, and the transition temperature increased as the bound Phe number decreased. Thus, the phase transition behavior of PAMAM-Phe-SO3Na dendrimers can be regulated by varying the Phe/PAMAM ratios.
Research and Development of High-Performance High-Damping Rubber Materials for High-Damping Rubber Isolation Bearings: A Review
Authors: Chen Bowen , Dai Junwu , Song Tingsu , Guan Qingsong
Published: June 2022

At present, high-damping rubber materials, widely used in the field of engineering seismic isolation, generally have the problems such as narrow effective damping temperature range, low damping loss factor and strong temperature dependence, which lead to prominent dependence of temperature and load conditions of the isolation performance of high-damping rubber isolation bearings. Research and development of high-performance high-damping rubber materials with broad effective damping temperature range, high damping loss factor and weak temperature dependence are very urgent and necessary to ensure the safety of the seismic isolation of engineering structures. This paper mainly reviews the recent progress in the research and development of high-damping rubber materials using nitrile butadiene rubber (NBR), epoxidized natural rubber (ENR), ethylene propylene diene rubber (EPDM), butyl rubber (IIR), chlorinated butyl rubber (CIIR), and bromine butyl rubber (BIIR). This is followed by a review of vulcanization and filler reinforcement systems for the improvement of damping and mechanical properties of high-damping rubber materials. Finally, it further reviews the constitutive models describing the hyperelasticity and viscoelasticity of rubber materials. In view of this focus, four key issues are highlighted for the development of high-performance high-damping rubber materials used for high-damping rubber isolation bearings.
Crosslinked Collagenic Scaffold Behavior Evaluation by Physico-Chemical, Mechanical and Biological Assessments in an In Vitro Microenvironment
Authors: Tihăuan Bianca-Maria , Pircalabioru Gratiela Gradisteanu , Axinie (Bucos) Mădălina , Marinaș Ioana Cristina , Nicoară Anca-Cecilia , Măruțescu Luminița , Oprea Ovidiu , Matei Elena , Maier Stelian Sergiu
Published: June 2022

Wound healing-associated difficulties continue to drive biotechnological creativeness into complex grounds. The sophisticated architecture of skin wound sites and the intricate processes involved in the response to the use of regenerative devices play a critical role in successful skin regeneration approaches and their possible outcomes. Due to a plethora of complications involved in wound healing processes as well as the coordination of various cellular mechanisms, biomimetic approaches seems to be the most promising starting ground. This study evaluates the behavior of a crosslinked, porous collagen scaffold obtained by lyophilization and dehydrothermal reticulation (DHT). We address the key physio-chemical and mechanical factors, such as swelling, density and porosity, mechano-dynamic properties, SEM and TG-DSC, as well as important biological outcomes regarding scaffold biocompatibility and cellular metabolic activity, cytokine expression in inflammation, apoptosis and necrosis, as well as hemocompatibility and biodegradation. The mechanical and visco-elastic behavior are correlated, with the samples found to present similar thermal behavior and increased rigidity after DHT treatment. High biocompatibility rates were obtained, with no inflammatory stimulation and a reduction in necrotic cells. Higher percentages of cellular early apoptosis were observed. The hemocompatibility rate was under 2%, coagulation effects expressed after 4 min, and the DHT scaffold was more resistant to the biodegradation of collagenase compared with the untreated sample.
Natural Fiber-Reinforced Thermoplastic ENR/PVC Composites as Potential Membrane Technology in Industrial Wastewater Treatment: A Review
Authors: Norfarhana A.S. , Ilyas R.A. , Ngadi N. , Sharma Shubham , Sayed Mohamed , El-Shafay A.S. , Nordin A.H.
Published: June 2022

Membrane separation processes are prevalent in industrial wastewater treatment because they are more effective than conventional methods at addressing global water issues. Consequently, the ideal membranes with high mechanical strength, thermal characteristics, flux, permeability, porosity, and solute removal capacity must be prepared to aid in the separation process for wastewater treatment. Rubber-based membranes have shown the potential for high mechanical properties in water separation processes to date. In addition, the excellent sustainable practice of natural fibers has attracted great attention from industrial players and researchers for the exploitation of polymer composite membranes to improve the balance between the environment and social and economic concerns. The incorporation of natural fiber in thermoplastic elastomer (TPE) as filler and pore former agent enhances the mechanical properties, and high separation efficiency characteristics of membrane composites are discussed. Furthermore, recent advancements in the fabrication technique of porous membranes affected the membrane’s structure, and the performance of wastewater treatment applications is reviewed.
Bioinspired High-Strength Montmorillonite-Alginate Hybrid Film: The Effect of Different Divalent Metal Cation Crosslinking
Authors: Wang Jiaen , Song Tianliang , Chen Huaxiang , Ming Wei , Cheng Zhiming , Liu Jingwen , Liang Benliang , Wang Yuting , Wang Guangsheng
Published: June 2022

The natural nacre has a regular ordered layered structure of calcium carbonate tablets and ion crosslinking proteins stacked alternately, showing outstanding mechanical properties. Inspired by nacre, we fabricated different divalent metal cation-crosslinked montmorillonite-alginate hybrid films (MMT-ALG-X2+; X2+ = Cu2+, Cd2+, Ba2+, Ca2+, Ni2+, Co2+ or Mn2+). The effect of ionic crosslinking strength and hydrogen bond interaction on the mechanical properties of the nacre-mimetics was studied. With the cations affinities with ALG being increased (Mn2+ < Co2+ = Ni2+ < Ca2+ < Ba2+ < Cd2+ < Cu2+), the tensile strength of nacre-mimetics showed two opposite influence trends: Weak ionic crosslinking (Mn2+, Co2+, Ni2+ and Ca2+) can synergize with hydrogen bonds to greatly increase the tensile properties of the sample; Strong ionic crosslinking (Ba2+, Cd2+, Cu2+) and hydrogen bonding form a competitive relationship, resulting in a rapid decrease in mechanical properties. Mn2+ crosslinking generates optimal strength of 288.0 ± 15.2 MPa with an ultimate strain of 5.35 ± 0.6%, obviously superior to natural nacre (135 MPa and 2%). These excellent mechanical properties arise from the optimum synergy of ion crosslinking and interfacial hydrogen bonds between crosslinked ALG and MMT nanosheets. In addition, these metal ion-crosslinked composite films show different colors, high visible transparency, and excellent UV shielding properties.
What the COVID-19 Pandemic Has Revealed about Religions
Authors: Lefebvre Solange
Published: June 2022

The beginning of year 2020 will be remembered as a turning point within several societies [...]
The Evolution of Chinese Muslim’s Classical Learning and Schools in the Ming and Qing Dynasties
Authors: Wang Wei
Published: June 2022

Around the middle of the Ming Dynasty, with the Chinese language becoming the mother tongue of Muslims in mainland China, the religious education of Chinese Muslims faced a dilemma. Meanwhile, a rejuvenated educational system was established by Hu Dengzhou (胡登洲) in Shaanxi during the Wanli (萬歷) period. This system, which was called Jingtang education (經堂教育) after a long time, has epoch-making significance in the history of Chinese Islamic thought. Through Hu Dengzhou’s disciples, this educational system gradually spread to North China and Jiangnan, where Shandong School and Jinling School were formed. Sufism played an important role in the two early schools’ teaching arrangements and academic activities. In the middle and late Qing periods, Shaanxi School and Yunnan School emerged one after another. Scholars of these two schools paid more attention to rational sciences represented by philosophical theology and attempted to use theological theories to explain Sufi texts. Overall, the establishment of Jingtang education was not only an urgent requirement for Muslims in mainland China to explain Islamic classics in Chinese, but also a fruitful attempt to replace official schools with private schools. The early Shandong School and Jinling School attached great importance to Sufism for two reasons: (1) Sufism became a prominent study after the 12th century, and most of the teachers of early Jingtang education had a close relationship with the Sufis. (2) These scholars live in a Chinese cultural background with Neo-Confucianism as the mainstream, and there are many commonalities between Sufism and Confucianism, which helps Muslim scholars to use Confucian terms to explain Islamic teaching. In the later period, Shaanxi School and Yunnan School turned to pay more attention to philosophical theology for two reasons: (1) In order to deal with the emergence and ideological differences of Chinese Islamic sects in the mid-Qing era. (2) This change was not unrelated to the influence of the Shixue (實學) thought trends in China, especially the Qianjia School.
Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet
Authors: Abdi Omid , Uusitalo Jori , Pietarinen Julius , Lajunen Antti
Published: June 2022

Accurate positioning is one of the main components and challenges for precision forestry. This study was established to test the feasibility of a low-cost GNSS receiver, u-blox ZED-F9P, in movable RTK mode with features that determine its positioning accuracy following logging trails in the forest environment. The accuracy of the low-cost receiver was controlled via a geodetic-grade receiver and high-density LiDAR data. The features of nearby logging trails were extracted from the LiDAR data in three main categories: tree characteristics; ground-surface conditions; and crown-surface conditions. An object-based TreeNet approach was used to explore the influential features of the receiver’s positioning accuracy. The results of the TreeNet model indicated that tree height, ground elevation, aspect, canopy-surface elevation, and tree density were the top influencing features. The partial dependence plots showed that tree height above 14 m, ground elevation above 134 m, western direction, canopy-surface elevation above 138 m, and tree density above 30% significantly increased positioning errors by the low-cost receiver over southern Finland. Overall, the low-cost receiver showed high performance in acquiring reliable and consistent positions, when integrated with LiDAR data. The system has a strong potential for navigating machinery in the pathway of precision harvesting in commercial forests.
Hyperspectral Band Selection via Optimal Combination Strategy
Authors: Li Shuying , Peng Baidong , Fang Long , Li Qiang
Published: June 2022

Band selection is one of the main methods of reducing the number of dimensions in a hyperspectral image. Recently, various methods have been proposed to address this issue. However, these methods usually obtain the band subset in the perspective of a locally optimal solution. To achieve an optimal solution with a global perspective, this paper developed a novel method for hyperspectral band selection via optimal combination strategy (OCS). The main contributions are as follows: (1) a subspace partitioning approach is proposed which can accurately obtain the partitioning points of the subspace. This ensures that similar bands can be divided into the same subspace; (2) two candidate representative bands with a large amount of information and high similarity are chosen from each subspace, which can fully represent all bands in the subspace; and (3) an optimal combination strategy is designed to acquire the optimal band subset, which achieves an optimal solution with a global perspective. The results on four public datasets illustrate that the proposed method achieves satisfactory performance against other methods.
Testing the Robust Yield Estimation Method for Winter Wheat, Corn, Rapeseed, and Sunflower with Different Vegetation Indices and Meteorological Data
Authors: Bognár Péter , Kern Anikó , Pásztor Szilárd , Steinbach Péter , Lichtenberger János
Published: June 2022

Remote sensing-based crop yield estimation methods rely on vegetation indices, which depend on the availability of the number of observations during the year, influencing the value of the derived crop yield. In the present study, a robust yield estimation method was improved for estimating the yield of corn, winter wheat, sunflower, and rapeseed in Hungary for the period 2000–2020 using 16 vegetation indices. Then, meteorological data were used to reduce the differences between the estimated and census yield data. In the case of corn, the best result was obtained using the Green Atmospherically Resistant Vegetation Index, where the correlation between estimated and census data was R2 = 0.888 before and R2 = 0.968 after the meteorological correction. In the case of winter wheat, the Difference Vegetation Index produced the best result with R2 = 0.815 and 0.894 before and after the meteorological correction. For sunflower, these correlation values were 0.730 and 0.880, and for rapeseed, 0.765 and 0.922, respectively. Using the meteorological correction, the average percentage differences between estimated and census data decreased from 7.7% to 3.9%, from 6.7% to 3.9%, from 7.2% to 4.2%, and from 7.8% to 5.1% in the case of corn, winter wheat, sunflower, and rapeseed, respectively.
Swin-Transformer-Enabled YOLOv5 with Attention Mechanism for Small Object Detection on Satellite Images
Authors: Gong Hang , Mu Tingkui , Li Qiuxia , Dai Haishan , Li Chunlai , He Zhiping , Wang Wenjing , Han Feng , Tuniyazi Abudusalamu , Li Haoyang , Lang Xuechan , Li Zhiyuan , Wang Bin
Published: June 2022

Object detection has made tremendous progress in natural images over the last decade. However, the results are hardly satisfactory when the natural image object detection algorithm is directly applied to satellite images. This is due to the intrinsic differences in the scale and orientation of objects generated by the bird’s-eye perspective of satellite photographs. Moreover, the background of satellite images is complex and the object area is small; as a result, small objects tend to be missing due to the challenge of feature extraction. Dense objects overlap and occlusion also affects the detection performance. Although the self-attention mechanism was introduced to detect small objects, the computational complexity increased with the image’s resolution. We modified the general one-stage detector YOLOv5 to adapt the satellite images to resolve the above problems. First, new feature fusion layers and a prediction head are added from the shallow layer for small object detection for the first time because it can maximally preserve the feature information. Second, the original convolutional prediction heads are replaced with Swin Transformer Prediction Heads (SPHs) for the first time. SPH represents an advanced self-attention mechanism whose shifted window design can reduce the computational complexity to linearity. Finally, Normalization-based Attention Modules (NAMs) are integrated into YOLOv5 to improve attention performance in a normalized way. The improved YOLOv5 is termed SPH-YOLOv5. It is evaluated on the NWPU-VHR10 dataset and DOTA dataset, which are widely used for satellite image object detection evaluations. Compared with the basal YOLOv5, SPH-YOLOv5 improves the mean Average Precision (mAP) by 0.071 on the DOTA dataset.
Estimating Leaf Chlorophyll Content of Moso Bamboo Based on Unmanned Aerial Vehicle Visible Images
Authors: Xu Huaixing , Wang Juzhong , Qu Yiling , Hu Lulu , Tang Yan , Zhou Zhongsheng , Xu Xiaojun , Zhou Yufeng
Published: June 2022

Leaf chlorophyll content is an important indicator of the physiological and ecological functions of plants. Accurate estimation of leaf chlorophyll content is necessary to understand energy, carbon, and water exchange between plants and the atmosphere. The leaf chlorophyll content index (CCI) of 109 Moso bamboo samples (19 for training data, 19 for validation data, and 71 for extrapolation data) was measured from December 2019 to May 2021, while their corresponding red–green–blue (RGB) images were acquired using an unmanned aerial vehicle (UAV) platform. A method for estimating leaf CCI based on constructing relationships between field leaf CCI measurements and UAV RGB images was evaluated. The results showed that a modified excess blue minus excess red index and 1.4 × H-S in the hue–saturation–value (HSV) color space were the most suitable variables for estimating the leaf CCI of Moso bamboo. No noticeable difference in accuracy between the linear regression model and backpropagation neural network (BPNN) model was found. Both models performed well in estimating leaf CCI, with an R2 > 0.85 and relative root mean square error (RMSEr) < 15.0% for the validation data. Both models failed to accurately estimate leaf CCI during the leaf-changing period (April to May in off-year), with the problems being overestimation in low leaf CCI and underestimation in high leaf CCI values. At a flight height of 120 m and illumination between 369 and 546 W/m2, the CCI for an independent sample dataset was accurately estimated by the models, with an R2 of 0.83 and RMSEr of 13.78%. Flight height and solar intensity played a role in increasing the generality of the models. This study provides a feasible and straightforward method to estimate the leaf CCI of Moso bamboo based on UAV RGB images.
Response of a Mesoscale Dipole Eddy to the Passage of a Tropical Cyclone: A Case Study Using Satellite Observations and Numerical Modeling
Authors: Huang Xiaorong , Wang Guihua
Published: June 2022

Mesoscale eddies occurring in the world’s oceans typically exist in pairs known as mesoscale dipole eddies or simply dipole eddies. Tropical cyclones (hereafter TCs) that move over the world’s oceans often encounter and interact with these dipole eddies. Through this interaction, TCs induce significant perturbations in the mesoscale eddies. However, the specific influences that the passage of a TC on a dipole eddy have not been addressed. In this paper, a case study of the dipole eddy’s response to the passage of a TC is conducted by using satellite observations and numerical simulation. The passage of a TC induces a long-duration response in the dipole eddy. First, the cyclonic ocean eddy component (COE) of the dipole is amplified, and the anticyclonic ocean eddy component (AOE) is weakened or even destroyed during the interaction. The amplification of the COE and weakening of the AOE primarily manifests as a change in their amplitudes and radii and as the adjustment of their vertical structure. The dipole eddy’s response to the interaction with a TC manifests as an upwelling anomaly and the injection of positive relative vorticity. Following the passage of the TC, the COE gradually stabilizes, and AOE slowly recovers after the disturbance energy from the interaction dissipates, which facilitates the reestablishment of the dipole eddy. The dipole reaches an equilibrium state through a quasi-geostrophic adjustment process. As a consequence, the overall effect of the interaction of the dipole with the TC leads to an asymmetric signature on the dipole eddy. The eddy–eddy interaction in a dipole may allow it to stabilize in a shorter time relative to that of a solitary eddy.
A Novel Intelligent Method Based on the Gaussian Heatmap Sampling Technique and Convolutional Neural Network for Landslide Susceptibility Mapping
Authors: Xiong Yibing , Zhou Yi , Wang Futao , Wang Shixin , Wang Zhenqing , Ji Jianwan , Wang Jingming , Zou Weijie , You Di , Qin Gang
Published: June 2022

Landslide susceptibility mapping (LSM) is significant for disaster prevention and mitigation, land use management, and as a reference for decision-making. Convolutional neural networks (CNNs) in deep learning have been successfully applied to LSM studies and have been shown to improve the accuracy of LSM. Although optimizing the quality of negative samples at the input step of a deep learning model can improve the accuracy of the model, the risk of model overfitting may increase. In this study, an LSM method based on the Gaussian heatmap sampling technique and a CNN was developed from the perspective of LSM dataset sampling. A Gaussian heatmap sampling technique was used to enrich the variety of landslide inventory at the input step of the deep learning model to improve the accuracy of the LSM results. This sampling technique involved the construction of a landslide susceptibility Gaussian heatmap neural network model, LSGH-Net, by combining a CNN. A series of optimization strategies such as attention mechanism, dropout, etc., were applied to improve the model structure and training process. The results demonstrated that the proposed approach outperformed the benchmark CNN-based algorithm in terms of metrics (Accuracy = 95.30%, F1 score = 95.13%, and Sensitivity = 91.79%). The Gaussian heatmap sampling technique effectively improved the accuracy of frequency histograms of the landslide susceptibility index, which provided finer-grained mapping details and more reasonable landslide density. By analyzing Gaussian heatmap at different scales, the approach proposed in this paper is an important reference for different regions and other disaster susceptibility studies as well.
A First Approach to Determine If It Is Possible to Delineate In-Season N Fertilization Maps for Wheat Using NDVI Derived from Sentinel-2
Authors: Uribeetxebarria Asier , Castellón Ander , Aizpurua Ana
Published: June 2022

Adjusting nitrogen fertilization to the nutritional requirements of crops is one of the major challenges of modern agriculture. The amount of N needed is mainly determined by crop yield, so yield maps can be used to optimize N fertilization. As the adoption of yield monitors is low among farmers, implementation of this approach is still low. However, as the Normalized Difference Vegetation Index (NDVI) is related to grain yield, the main objective of this work was to identify at which wheat growth stage a moderate agreement between NDVI and yield is obtained. For this, NDVI images obtained from Sentinel-2 were used, and the evolution of concordance was analyzed in 13 classified parcels of wheat employing the Kappa index (KI). In one-third of the plots, a moderate agreement (KI > 0.4) was reached before the stem elongation growth phase (when the last N application was made). In another one-third, moderate agreement was reached later, in more advanced development stages. For the cases in which this agreement did not exist, an attempt was made to find the causes. The MANOVA and subsequent descriptive discriminant analysis (DDA) showed that the NDVI dates that contribute the most to the differentiation between plots with and without agreement between grain yield maps and NDVI images were those corresponding to tillering. The sum of the NDVI values of the tillering phase was significantly lower in the group of plots that did not show concordance. Sentinel-2 imagery was successful on 66% of plots for delineation of management zones after GS 30, and thus is useful for producing fertilization maps for the upcoming season. However, to produce in-season fertilization maps, further studies are needed to better understand the mechanisms that regulate the relation between yield and NDVI at early growth stages (<GS 30).
Machine-Learning-Based Change Detection of Newly Constructed Areas from GF-2 Imagery in Nanjing, China
Authors: Zhou Shuting , Dong Zhen , Wang Guojie
Published: June 2022

Change detection of the newly constructed areas (NCAs) is important for urban development. The advances of remote sensing and deep learning algorithms promotes the high precision of the research work. In this study, we firstly constructed a high-resolution labels for change detection based on the GF-2 satellite images, and then applied five deep learning models of change detection, including STANets (BASE, BAM, and PAM), SNUNet (Siam-NestedUNet), and BiT (Bitemporal image Transformer) in the Core Region of Jiangbei New Area of Nanjing, China. The BiT model is based on transformer, and the others are based on CNN (Conventional Neural Network). Experiments have revealed that the STANet-PAM model generally performs the best in detecting the NCAs, and the STANet-PAM model can obtain more detailed information of land changes owing to its pyramid spatial-temporal attention module of multiple scales. At last, we have used the five models to analyze urbanization processes from 2015 to 2021 in the study area. Hopefully, the results of this study could be a momentous reference for urban development planning.
Assessing Land Subsidence-Inducing Factors in the Shandong Province, China, by Using PS-InSAR Measurements
Authors: Li Fengkai , Liu Guolin , Gong Huili , Chen Beibei , Zhou Chaofan
Published: June 2022

Shandong Province (SDP) experienced serious land subsidence from March 2017 to December 2020. Exploring the response relationships between land subsidence and its inducing factors plays an important role in ensuring the development of the economy and residential safety. Firstly, we applied Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology to 558 Sentinel-1 images to determine the land subsidence in SDP from March 2017 to December 2020. Secondly, we mosaicked the land subsidence monitoring results of five tracks to obtain a land subsidence map covering the whole SDP and validated the land subsidence monitoring results using Global Positioning System (GPS) monitoring results and leveling benchmark monitoring results observed in the same period. Finally, the response relationships between the land subsidence and its inducing factors in SDP were analyzed. The findings are as follows: (1) the PS-InSAR outcomes showed that the land subsidence was widely distributed in SDP and that the maximum land subsidence rate was −298.9 mm/year during the study period. (2) The PS-InSAR monitoring results coincide well with the GPS monitoring results and leveling benchmark monitoring results; the Pearson correlation coefficient (PCC) values between the PS-InSAR monitoring results and the GPS measurement results and leveling benchmark monitoring results were 0.97 and 0.98, respectively. We found that Spearman’s rank correlation coefficient (SRCC) values between any two adjacent tracks of the mosaic PS-InSAR monitoring results were greater than 0.95, indicating good consistency. (3) The long-term overexploitation of groundwater in middle and deep aquifers and mining of underground mineral resources are the main inducing factors of land subsidence in SDP when considering this problem on a large geographical scale. Moreover, the type of bridge material is an important inducing factor causing the large variation in the land subsidence of the bridge body within a small geographical range. These findings may provide scientific support for land subsidence control measures in SDP.
Estimation of the Block Adjustment Error in UAV Photogrammetric Flights in Flat Areas
Authors: Arévalo-Verjel Alba Nely , Lerma José Luis , Prieto Juan F. , Carbonell-Rivera Juan Pedro , Fernández José
Published: June 2022

UAV-DAP (unmanned aerial vehicle-digital aerial photogrammetry) has become one of the most widely used geomatics techniques in the last decade due to its low cost and capacity to generate high-density point clouds, thus demonstrating its great potential for delivering high-precision products with a spatial resolution of centimetres. The questions is, how should it be applied to obtain the best results? This research explores different flat scenarios to analyse the accuracy of this type of survey based on photogrammetric SfM (structure from motion) technology, flight planning with ground control points (GCPs), and the combination of forward and cross strips, up to the point of processing. The RMSE (root mean square error) is analysed for each scenario to verify the quality of the results. An equation is adjusted to estimate the a priori accuracy of the photogrammetric survey with digital sensors, identifying the best option for μxyz (weight coefficients depending on the layout of both the GCP and the image network) for the four scenarios studied. The UAV flights were made in Lorca (Murcia, Spain). The study area has an extension of 80 ha, which was divided into four blocks. The GCPs and checkpoints (ChPs) were measured using dual-frequency GNSS (global navigation satellite system), with a tripod and centring system on the mark at the indicated point. The photographs were post-processed using the Agisoft Metashape Professional software (64 bits). The flights were made with two multirotor UAVs, a Phantom 3 Professional and an Inspire 2, with a Zenmuse X5S camera. We verify the influence by including additional forward and/or cross strips combined with four GCPs in the corners, plus one additional GCP in the centre, in order to obtain better photogrammetric adjustments based on the preliminary flight planning.
Fully Textile Dual-Band Logo Antenna for IoT Wearable Devices
Authors: Atanasova Gabriela Lachezarova , Atanasov Blagovest Nikolaev , Atanasov Nikolay Todorov
Published: June 2022

In recent years, the interest in the Internet of Things (IoT) has been growing because this technology bridges the gap between the physical and virtual world, by connecting different objects and people through communication networks, in order to improve the quality of life. New IoT wearable devices require new types of antennas with unique shapes, made on unconventional substrates, which can be unobtrusively integrated into clothes and accessories. In this paper, we propose a fully textile dual-band logo antenna integrated with a reflector for application in IoT wearable devices. The proposed antenna’s radiating elements have been shaped to mimic the logo of South-West University “Neofit Rilski” for an unobtrusive integration in accessories. A reflector has been mounted on the opposite side of the textile substrate to reduce the radiation from the wearable antenna and improve its robustness against the loading effect from nearby objects. Two antenna prototypes were fabricated and tested in free space as well as on three different objects (human body, notebook, and laptop). Moreover, in the two frequency ranges of interest a radiation efficiency of 25–38% and 62–90% was achieved. Moreover, due to the reflector, the maximum local specific-absorption rate, which averaged over 10 g mass in the human-body phantom, was found to be equal to 0.5182 W/kg at 2.4 GHz and 0.16379 W/kg at 5.47 GHz. Additionally, the results from the performed measurement-campaign collecting received the signal-strength indicator and packet loss for an off-body scenario in real-world use, demonstrating that the backpack-integrated antenna prototype can form high-quality off-body communication channels.
Fast Route Planner Considering Terrain Information
Authors: Kim Jonghoek
Published: June 2022

Route planning considering terrain information is useful for the navigation of autonomous ground vehicles (AGV) on complicated terrain surfaces, such as mountains with rivers. For instance, an AGV in mountains cannot cross a river or a valley that is too steep. This article addresses a novel route-planning algorithm that is time-efficient in building a sub-optimal route considering terrain information. In order to construct a route from the start to the end point in a time-efficient manner, we simulate two virtual vehicles that deploy virtual nodes iteratively, such that the connected node network can be formed. The generated node network serves as a topological map for a real AGV, and we construct the shortest route from the start to the end point utilizing the network. The route is weighted considering the route length, the steepness of the route, and the traversibility of the route. Through MATLAB simulations, we demonstrate the effectiveness of the proposed route-planning algorithm by comparing it with RRT-star planners.
Multiple Concurrent Slotframe Scheduling for Wireless Power Transfer-Enabled Wireless Sensor Networks
Authors: Lee Sol-Bee , Nguyen-Xuan Sam , Kwon Jung-Hyok , Kim Eui-Jik
Published: June 2022

This paper presents a multiple concurrent slotframe scheduling (MCSS) protocol for wireless power transfer (WPT)-enabled wireless sensor networks. The MCSS supports a cluster-tree network topology composed of heterogeneous devices, including hybrid access points (HAPs) serving as power transmitting units and sensor nodes serving as power receiving units as well as various types of traffic, such as power, data, and control messages (CMs). To this end, MCSS defines three types of time-slotted channel hopping (TSCH) concurrent slotframes: the CM slotframe, HAP slotframe, and WPT slotframe. These slotframes are used for CM traffic, inter-cluster traffic, and intra-cluster traffic, respectively. In MCSS, the length of each TSCH concurrent slotframe is set to be mutually prime to minimize the overlap between cells allocated in the slotframes, and its transmission priority is determined according to the characteristics of transmitted traffic. In addition, MCSS determines the WPT slotframe length, considering the minimum number of power and data cells required for energy harvesting and data transmission of sensor nodes and the number of overprovisioned cells needed to compensate for overlap between cells. The simulation results demonstrated that MCSS outperforms the legacy TSCH medium access control protocol and TSCH multiple slotframe scheduling (TMSS) for the average end-to-end delay, aggregate throughput, and average harvested energy.
Blockchain-Based Smart Home Networks Security Empowered with Fused Machine Learning
Authors: Farooq Muhammad Sajid , Khan Safiullah , Rehman Abdur , Abbas Sagheer , Khan Muhammad Adnan , Hwang Seong Oun
Published: June 2022

Security and privacy in the Internet of Things (IoT) other significant challenges, primarily because of the vast scale and deployment of IoT networks. Blockchain-based solutions support decentralized protection and privacy. In this study, a private blockchain-based smart home network architecture for estimating intrusion detection empowered with a Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system model is proposed. This study investigates the methodology of RTS-DELM implemented in blockchain-based smart homes to detect any malicious activity. The approach of data fusion and the decision level fusion technique are also implemented to achieve enhanced accuracy. This study examines the numerous key components and features of the smart home network framework more extensively. The Fused RTS-DELM technique achieves a very significant level of stability with a low error rate for any intrusion activity in smart home networks. The simulation findings indicate that this suggested technique successfully optimizes smart home networks for monitoring and detecting harmful or intrusive activities.