bluuebunny/crossref_metadata_2025 huggingface dataset:
One-Week Scutellar Somatic Embryogenesis in the Monocot Brachypodium distachyon
Authors: Wehbi Houssein , Soulhat Camille , Morin Halima , Bendahmane Abdelhafid , Hilson Pierre , Bouchabké-Coussa Oumaya
Published: April 2022

Plant somatic embryogenesis (SE) is a natural process of vegetative propagation. It can be induced in tissue cultures to investigate developmental transitions, to create transgenic or edited lines, or to multiply valuable crops. We studied the induction of SE in the scutellum of monocots with Brachypodium distachyon as a model system. Towards the in-depth analysis of SE initiation, we determined the earliest stages at which somatic scutellar cells acquired an embryogenic fate, then switched to a morphogenetic mode in a regeneration sequence involving treatments with exogenous hormones: first an auxin (2,4-D) then a cytokinin (kinetin). Our observations indicated that secondary somatic embryos could already develop in the proliferative calli derived from immature zygotic embryo tissues within one week from the start of in vitro culture. Cell states and tissue identity were deduced from detailed histological examination, and in situ hybridization was performed to map the expression of key developmental genes. The fast SE induction method we describe here facilitates the mechanistic study of the processes involved and may significantly shorten the production of transgenic or gene-edited plants.
Low Concentration of Anti-Auxin and Anti-Fungal Agent Accelerates the PLB Regeneration of Dendrobium okinawense under Green LED
Authors: Mehbub Hasan , Shimasaki Kazuhiko , Mehraj Hasan
Published: April 2022

Dendrobium okinawense is an endangered epiphytic orchid, and there has been no scientific report so far on its propagation. Protocorm is a mass of cells, and protocorm-like bodies (PLBs) are lookalike protocorms produced by vegetative explants in vitro. Regeneration of PLBs is a widely used technique for orchid micropropagation. We used different light-emitting diodes (LEDs) for the PLB regeneration of D. okinawense. The number of PLBs and fresh weight were increased by 81.1% and 80.8%, respectively, under green LED over the white fluorescent (WF) light. We added different concentrations of PCIB (p-Chlorophenoxyisobutyric acid, an anti-auxin) and HMI (3-Hydroxy-5-methyl isoxazole, an anti-fungal agent) in culture media. The number of PLBs was increased in media having 0.01 mg/L of PCIB (35.9%) compared to control (no PCIB), whereas 19.3% increased in media having 0.01 mL/L of HMI compared to control (no HMI). Green LED in combination with 0.01 mg/L of PCIB significantly increased the number of PLBs (69.0%) compared to the WF–without PCIB combination. In LEDs-PCIB and LED-HMI combinations, HMI did not show better PLBs regeneration compared with PCIB. The results suggested that a combination of low concentrations of PCIB and green LED have the potential to accelerate PLB regeneration of D. okinawense.
Iodo Silanes as Superior Substrates for the Solid Phase Synthesis of Molecularly Imprinted Polymer Nanoparticles
Authors: Piletsky Stanislav S. , Garcia Cruz Alvaro , Piletska Elena , Piletsky Sergey A. , Aboagye Eric O. , Spivey Alan C.
Published: April 2022

Current state-of-the-art techniques for the solid phase synthesis of molecularly imprinted polymer (MIP) nanoparticles typically rely on amino silanes for the immobilisation of template molecules prior to polymerisation. An investigation into commonly used amino silanes identified a number of problematic side reactions which negatively affect the purity and affinity of these polymers. Iodo silanes are presented as a superior alternative in a case study describing the synthesis of MIPs against epitopes of a common cancer biomarker, epidermal growth factor receptor (EGFR). The proposed iodo silane outperformed the amino silane by all metrics tested, showing high purity and specificity, and nanomolar affinity for the target peptide.
A Phosphorous-Containing Bio-Based Furfurylamine Type Benzoxazine and Its Application in Bisphenol-A Type Benzoxazine Resins: Preparation, Thermal Properties and Flammability
Authors: Zhao Chunxia , Sun Zhangmei , Wei Jixuan , Li Yuntao , Xiang Dong , Wu Yuanpeng , Que Yusheng
Published: April 2022

Polybenzoxazine (PBa) composites based on phosphorous-containing bio-based furfurylamine type benzoxazines (D-fu) and bisphenol-A type benzoxazines (Ba) were developed for flame retardation. The structure of D-fu was analyzed by Fourier transform infrared (FTIR) spectroscopy and 1H-NMR spectroscopy. The curing temperature of Ba/D-fu mixtures was systematically studied by differential scanning calorimetry (DSC). Thermogravimetric analysis (TGA) demonstrated the excellent char formation ability of the PBa composites with the addition of phosphorous-containing D-fu. The flame retardancy of the PBa composite materials was tested by the limited oxygen index (LOI), vertical burning test (UL-94) and cone calorimeter (CONE). The LOI and UL-94 level of PBa/PD-fu-5% reached 34 and V0 rate, respectively. Notably, the incorporation of 5% D-fu into PBa led to a decrease of 21.9% at the peak of the heat-release rate and a mass-loss reduction of 8.0%. Moreover, the fire performance index increased, which demonstrated that the introduction of D-fu can diminish fire occurrence. The role of D-fu in the condensed and gas phases for the fire-resistant mechanism of the PBa matrix was supported by SEM-EDS and TGA/infrared spectrometry (TG-FTIR), respectively. Dynamic mechanical analysis (DMA) revealed that the Tg of PBa flame-retardant composites was around 230 °C. Therefore, PBa composites are promising fire-retardant polymers that can be applied as high-performance functional materials.
Recent Trends in Protective Textiles against Biological Threats: A Focus on Biological Warfare Agents
Authors: Antunes Joana C. , Moreira Inês P. , Gomes Fernanda , Cunha Fernando , Henriques Mariana , Fangueiro Raúl
Published: April 2022

The rising threats to worldwide security (affecting the military, first responders, and civilians) urge us to develop efficient and versatile technological solutions to protect human beings. Soldiers, medical personnel, firefighters, and law enforcement officers should be adequately protected, so that their exposure to biological warfare agents (BWAs) is minimized, and infectious microorganisms cannot be spread so easily. Current bioprotective military garments include multilayered fabrics integrating activated carbon as a sorptive agent and a separate filtrating layer for passive protection. However, secondary contaminants emerge following their accumulation within the carbon filler. The clothing becomes too heavy and warm to wear, not breathable even, preventing the wearer from working for extended hours. Hence, a strong need exists to select and/or create selectively permeable layered fibrous structures with bioactive agents that offer an efficient filtering capability and biocidal skills, ensuring lightweightness, comfort, and multifunctionality. This review aims to showcase the main possibilities and trends of bioprotective textiles, focusing on metal–organic frameworks (MOFs), inorganic nanoparticles (e.g., ZnO-based), and organic players such as chitosan (CS)-based small-scale particles and plant-derived compounds as bioactive agents. The textile itself should be further evaluated as the foundation for the barrier effect and in terms of comfort. The outputs of a thorough, standardized characterization should dictate the best elements for each approach.
Thermal Degradation of Photoluminescence Poly(9,9-dioctylfluorene) Solvent-Tuned Aggregate Films
Authors: Chew Kang Wei , Abdul Rahim Nor Azura , Teh Pei Leng , Abdul Hisam Nurfatin Syafiqah , Alias Siti Salwa
Published: April 2022

The progression of the green emission spectrum during the decomposition of polyfluorenes (PFs) has impeded the development and commercialization of the materials. Herein, we constructed a solvent-tuned aggregated PFO film with the aim of retarding the material’s thermal degradation behavior which causes a significant decline in optical properties as a result of phase transformation. The tuning of the aggregate amount and distribution was executed by applying a poor alcohol-based solvent in chloroform. It emerges that at a lower boiling point methanol evaporates quickly, limiting the aggregate propagation in the film which gives rise to a more transparent film. Furthermore, because of the modulated β-phase conformation, the absorption spectra of PFO films were red-shifted and broadened. The increase in methanol percentage also led to a rise in β-phase percentage. As for the thermal degradation reactions, both pristine and aggregated PFO films exhibited apparent changes in the UV-Vis spectra and PL spectra. In addition, a 97:3 (chloroform:methanol) aggregated PFO film showed a more defined emission spectrum, which demonstrates that the existence of β-phase is able to suppress the unwanted green emission.
Cold Plasma-Based Fabrication and Characterization of Active Films Containing Different Types of Myristica fragrans Essential Oil Emulsion
Authors: Yudhistira Bara , Sulaimana Andi Syahrullah , Punthi Fuangfah , Chang Chao-Kai , Lung Chun-Ta , Santoso Shella Permatasari , Gavahian Mohsen , Hsieh Chang-Wei
Published: April 2022

Myristica fragrans essential oil (MFEO) is a potential active compound for application as an active packaging material. A new approach was developed using a cold plasma treatment to incorporate MFEO to improve the optical, physical, and bacterial inhibition properties of the film. The MFEO was added as coarse emulsion (CE), nanoemulsion (NE), and Pickering emulsion (PE) at different concentrations. The PE significantly affected (p < 0.05) the optical, physical, and chemical properties compared with CE and NE films. The addition of MFEO to low-density polyethylene (LDPE) film significantly reduced water vapor permeability (WVP) and oxygen permeability (OP) and showed marked activity against E. coli and S. aureus (p < 0.05). The release rate of PE films after 30 h was 70% lower than that of CE and NE films. Thus, it can be concluded that the fabrication of active packaging containing MFEO is a potential food packaging material.
Tailoring the Barrier Properties of PLA: A State-of-the-Art Review for Food Packaging Applications
Authors: Marano Stefania , Laudadio Emiliano , Minnelli Cristina , Stipa Pierluigi
Published: April 2022

It is now well recognized that the production of petroleum-based packaging materials has created serious ecological problems for the environment due to their resistance to biodegradation. In this context, substantial research efforts have been made to promote the use of biodegradable films as sustainable alternatives to conventionally used packaging materials. Among several biopolymers, poly(lactide) (PLA) has found early application in the food industry thanks to its promising properties and is currently one of the most industrially produced bioplastics. However, more efforts are needed to enhance its performance and expand its applicability in this field, as packaging materials need to meet precise functional requirements such as suitable thermal, mechanical, and gas barrier properties. In particular, improving the mass transfer properties of materials to water vapor, oxygen, and/or carbon dioxide plays a very important role in maintaining food quality and safety, as the rate of typical food degradation reactions (i.e., oxidation, microbial development, and physical reactions) can be greatly reduced. Since most reviews dealing with the properties of PLA have mainly focused on strategies to improve its thermal and mechanical properties, this work aims to review relevant strategies to tailor the barrier properties of PLA-based materials, with the ultimate goal of providing a general guide for the design of PLA-based packaging materials with the desired mass transfer properties.
Green and Rapid Preparation of Fluorosilicone Rubber Foam Materials with Tunable Chemical Resistance for Efficient Oil–Water Separation
Authors: Hu Wan-Jun , Xia Qiao-Qi , Pan Hong-Tao , Chen Hai-Yang , Qu Yong-Xiang , Chen Zuan-Yu , Zhang Guo-Dong , Zhao Li , Gong Li-Xiu , Xue Chang-Guo , Tang Long-Cheng
Published: April 2022

Polydimethylsiloxane (PDMS) foam materials with lightweight, excellent oil resistance and mechanical flexibility are highly needed for various practical applications in aerospace, transportation, and oil/water separation. However, traditional PDMS foam materials usually present poor chemical resistance and easily swell in various solvents, which greatly limits their potential application. Herein, novel fluorosilicone rubber foam (FSiRF) materials with different contents of trifluoropropyl lateral groups were designed and fabricated by a green (no solvents used) and rapid (<10 min foaming process) foaming/crosslinking approach at ambient temperature. Typically, vinyl-terminated poly(dimethyl-co-methyltrifluoropropyl) siloxanes with different fluorine contents of 0–50 mol% were obtained through ring-opening polymerization to effectively adjust the chemical resistance of the FSiRFs. Notably, the optimized FSiRF samples exhibit lightweight (~0.25 g/cm−3), excellent hydrophobicity/oleophilicity (WCA > 120°), reliable mechanical flexibility (complete recovery ability after stretching of 130% strain or compressing of >60%), and improved chemical resistance and structural stability in various solvents, making them promising candidates for efficient and continuous oil–water separation. This work provides an innovative concept to design and prepare advanced fluorosilicone rubber foam materials with excellent chemical resistance for potential oil–water separation application.
Effect of Dietary Choline Chloride Supplementation on Growth Performance and Carcass Characteristics of Broiler Chickens Reared to 32 Days of Age
Authors: Gregg Caroline R. , Tejeda Oscar J. , Spencer Lindsey F. , Calderon Allan J. , Bourassa Dianna V. , Starkey Jessica D. , Starkey Charles W.
Published: April 2022

Research on the impact of supplementing additional dietary choline to modern, large-frame broiler chickens is limited, and current choline recommendations are outdated. The objective of this study was to determine the effect of additional dietary choline chloride supplementation on growth performance and carcass characteristics of modern broilers reared to 32 days of age. Corn and soybean meal-based diets were formulated to contain an additional 0, 400, 800, 1200, 1600, or 2000 mg of choline chloride per kg of feed above the choline present in the basal diet ingredients. As-hatched Ross 708 × Yield Plus broiler chicks (n = 2160; 30 birds per pen; 44 ± 0.2 g initial BW) were randomly allotted to the experimental diets, reared for 31 days, and processed at day 32. Growth performance, carcass yield, and breast myopathy incidence were not impacted by supplemental choline. However, abdominal fat pad weight tended to diminish with increasing dietary choline, and drumstick yield was reduced in birds fed over 800 mg per kg of feed. These results indicate feeding additional choline does not impact growth performance but may result in changes in carcass characteristics of modern, high-yielding broilers reared for 32 days.
Quaternary Evolutionary Stages of Selinitsa Cave (SW Peloponnese, Greece) Reveal Sea-Level Changes Based on 3D Scanning, Geomorphological, Biological, and Sedimentological Indicators
Authors: Kampolis Isidoros , Triantafyllidis Stavros , Skliros Vasilios , Kamperis Evangelos
Published: April 2022

Significant evolutionary stages of Selinitsa Cave (SW Peloponnese, Greece) were revealed by 3D mapping, as well as geomorphological study of the cave and the nearby landscape. Four marine terraces were identified in the area of the coastal cave at 6, 10.7, 16.6, and 30–32 m above sea level (asl), with the terrace at 16.6 m representing Marine Isotope Stage (MIS) 5. The widest karstified space of Selinitsa Cave clusters between 15.73 and 18.05 m above sea level (asl), with the peak lying at 16.4 m asl, corresponding to the level where the phreatic/epiphreatic zone was stable for a sufficient period of time. A tidal notch at 16.4 m asl at the cave entrance is correlated to the marine terrace at 16.6 m. Both features correspond to the sea-level stand at which intense karstification occurred. The tidal notch bears a horizontal arrangement of Lithophaga borings at the vertex. Sedimentological investigation of the Selinitsa fine-grained deposit revealed the paleohydrologic regime of the cave. It is characterized by “slack-water” facies, indicating very low water flow speeds, whereas the thickness of the deposit points to stable hydrological conditions for prolonged periods. The cave sediment height of 18.8 m asl indicates a flooding level higher than sea level. The overlying Plattenkalk flysch is most probably the major source of detritus, and the predominance of authigenic dolomite (>98% modal in the carbonate fraction) indicates a hyposaline environment related to mixing of sea water with percolating fresh water. The approach of this study shows the significance of 3D mapping, bio-geo-Relative Sea Level (RSL) indicators, and sedimentology in deciphering the paleogeographic evolution of coastal karstic systems and subsequently defining the paleoclimate regime of coastal areas in Greece and the eastern Mediterranean during the Late Quaternary.
Spatial and Temporal Inversion of Land Surface Temperature along Coastal Cities in Arid Regions
Authors: Al-Ruzouq Rami , Shanableh Abdallah , Khalil Mohamad Ali , Zeiada Waleed , Hamad Khaled , Abu Dabous Saleh , Gibril Mohamed Barakat A. , Al-Khayyat Ghadeer , Kaloush Kamil E. , Al-Mansoori Saeed , Jena Ratiranjan
Published: April 2022

Climate change is undoubtedly affecting the global weather of the Earth. Rapid human civilization has mainly caused this in the last few decades. This research examined the spatial and temporal land surface temperature (LST) in the United Arab Emirates (UAE) coastal cities located in an arid region that faced massive urbanization over the last 50 years. We estimated the LST using by-products of Landsat and MODIS images covering 2000 until 2020. The assessment of LST was performed in two contexts, i.e., spatially and temporally, covering daytime vs. nighttime during the summer and winter seasons. Additionally, a supervised classification technique was adopted to extract the land use and land cover in the study area from the late 1970s until 2018. Unexpectedly, the results indicated that daytime LST in districts near the coastlines (heavily urbanized areas) are lower than the ones far away from the coast (about 9 °C). This observation represents the spatial LST inversion in the study area. Nevertheless, this difference was not observed during nighttime LST temporally, the daytime LST did not increase significantly during either summer or winter seasons. However, the nighttime LST has increased temporally by about 17% since 2000 (the temporal LST inversion). Both LST inversions could be attributed to the uniqueness of the study area, given that bare land desert was replaced by vegetation, high-rise buildings, and industrial activities. Additionally, the wind breeze blowing from the gulf might potentially contribute to cooling the coastal urban area during the daytime. Furthermore, in-depth zonal statistics were conducted to visualize the effect of land use on LST. The study observed that fully built-up areas with vegetation have lower LST than built-up areas without vegetation or a combination of sand and vegetation. The research outcomes are invaluable for decision-makers and researchers in achieving sustainable urban development.
Statistical and Machine Learning Models for Remote Sensing Data Mining—Recent Advancements
Authors: Das Monidipa , Ghosh Soumya K. , Chowdary Vemuri M. , Mitra Pabitra , Rijal Santosh
Published: April 2022

During the last few decades, the remarkable progress in the field of satellite remote sensing (RS) technology has enabled us to capture coarse, moderate to high-resolution earth imagery on weekly, daily, and even hourly intervals [...]
Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian
Authors: Jardim Alexandre Maniçoba da Rosa Ferraz , Araújo Júnior George do Nascimento , Silva Marcos Vinícius da , Santos Anderson dos , Silva Jhon Lennon Bezerra da , Pandorfi Héliton , Oliveira-Júnior José Francisco de , Teixeira Antônio Heriberto de Castro , Teodoro Paulo Eduardo , de Lima João L. M. P. , Silva Junior Carlos Antonio da , Souza Luciana Sandra Bastos de , Silva Emanuel Araújo , Silva Thieres George Freire da
Published: April 2022

Caatinga biome, located in the Brazilian semi-arid region, is the most populous semi-arid region in the world, causing intensification in land degradation and loss of biodiversity over time. The main objective of this paper is to determine and analyze the changes in land cover and use, over time, on the biophysical parameters in the Caatinga biome in the semi-arid region of Brazil using remote sensing. Landsat-8 images were used, along with the Surface Energy Balance Algorithm for Land (SEBAL) in the Google Earth Engine platform, from 2013 to 2019, through spatiotemporal modeling of vegetation indices, i.e., leaf area index (LAI) and vegetation cover (VC). Moreover, land surface temperature (LST) and actual evapotranspiration (ETa) in Petrolina, the semi-arid region of Brazil, was used. The principal component analysis was used to select descriptive variables and multiple regression analysis to predict ETa. The results indicated significant effects of land use and land cover changes on energy balances over time. In 2013, 70.2% of the study area was composed of Caatinga, while the lowest percentages were identified in 2015 (67.8%) and 2017 (68.7%). Rainfall records in 2013 ranged from 270 to 480 mm, with values higher than 410 mm in 46.5% of the study area, concentrated in the northern part of the municipality. On the other hand, in 2017 the lowest annual rainfall values (from 200 to 340 mm) occurred. Low vegetation cover rate was observed by LAI and VC values, with a range of 0 to 25% vegetation cover in 52.3% of the area, which exposes the effects of the dry season on vegetation. The highest LST was mainly found in urban areas and/or exposed soil. In 2013, 40.5% of the region’s area had LST between 48.0 and 52.0 °C, raising ETa rates (~4.7 mm day−1). Our model has shown good outcomes in terms of accuracy and concordance (coefficient of determination = 0.98, root mean square error = 0.498, and Lin’s concordance correlation coefficient = 0.907). The significant increase in agricultural areas has resulted in the progressive reduction of the Caatinga biome. Therefore, mitigation and sustainable planning is vital to decrease the impacts of anthropic actions.
Unsupervised Building Extraction from Multimodal Aerial Data Based on Accurate Vegetation Removal and Image Feature Consistency Constraint
Authors: Meng Yan , Chen Shanxiong , Liu Yuxuan , Li Li , Zhang Zemin , Ke Tao , Hu Xiangyun
Published: April 2022

Accurate building extraction from remotely sensed data is difficult to perform automatically because of the complex environments and the complex shapes, colours and textures of buildings. Supervised deep-learning-based methods offer a possible solution to solve this problem. However, these methods generally require many high-quality, manually labelled samples to obtain satisfactory test results, and their production is time and labour intensive. For multimodal data with sufficient information, extracting buildings accurately in as unsupervised a manner as possible. Combining remote sensing images and LiDAR point clouds for unsupervised building extraction is not a new idea, but existing methods often experience two problems: (1) the accuracy of vegetation detection is often not high, which leads to limited building extraction accuracy, and (2) they lack a proper mechanism to further refine the building masks. We propose two methods to address these problems, combining aerial images and aerial LiDAR point clouds. First, we improve two recently developed vegetation detection methods to generate accurate initial building masks. We then refine the building masks based on the image feature consistency constraint, which can replace inaccurate LiDAR-derived boundaries with accurate image-based boundaries, remove the remaining vegetation points and recover some missing building points. Our methods do not require manual parameter tuning or manual data labelling, but still exhibit a competitive performance compared to 29 methods: our methods exhibit accuracies higher than or comparable to 19 state-of-the-art methods (including 8 deep-learning-based methods and 11 unsupervised methods, and 9 of them combine remote sensing images and 3D data), and outperform the top 10 methods (4 of them combine remote sensing images and LiDAR data) evaluated using all three test areas of the Vaihingen dataset on the official website of the ISPRS Test Project on Urban Classification and 3D Building Reconstruction in average area quality. These comparative results verify that our unsupervised methods combining multisource data are very effective.
New Chung-Li Ionosonde in Taiwan: System Description and Preliminary Results
Authors: Ke Kai-Jun , Su Ching-Lun , Kuong Ruey-Ming , Chen Hsyang-Chan , Lin Hung-Shi , Chiu Po-Hsun , Ko Ching-Yuan , Chu Yen-Hsyang
Published: April 2022

In spite of being interrupted several times in its long history of operation since 1950, the routine observation of the ionosphere with various ionosondes installed at the Chung-Li ionosphere station in Taiwan has been achieved successively for more than seven decades. In this article, the system characteristics of the latest Chung-Li ionosonde and algorithm developed by National Central University for ionogram scaling and true height analysis, which started to routinely operate in 2020, are introduced. The new Chung-Li ionosonde is a pulse radar that transmits a train of short pulses with respective carrier frequencies between 2 and 30 MHz at a frequency separation of 50 kHz. The duration of an entire frequency sweep is 294.13 s, which is divided into 561 frequency channels. The 16-bit complementary code is employed to increase the signal-to-noise of the reflected echoes. The observational range is from 70 to 1221 km with a range resolution of 3.84 km. We developed an algorithm for the Chung-Li ionosonde to automatically scale the ionogram such that the true height profile of the ionospheric electron density can be retrieved. The observed traces of the ordinary wave (O-wave) and extraordinary wave (X-wave) displayed on the ionogram were first identified and separated by using 2-dimensional autocorrelation analysis combined with the image projection method. The true height analysis used stepwise regression. With the help of the International Reference Ionosphere (IRI) model and Quasi-Parabolic Segment (QPS) model, we carried out true height analysis to retrieve the ionospheric electron density profile based on the O-wave trace. An examination showed that the ionospheric parameters (i.e., foF2, h’F2) retrieved from the automatic scaling algorithm were essentially in good agreement with those obtained from manual scaling. The ionosonde-measured foF2 and hmF2 were also compared with the FORMOSAT-7 measurements made with the GPS radio occultation technique. The results show that the correlation coefficient, root mean squared deviation, and mean difference were, respectively, in ranges from 0.878 to 0.93, 0.73 to 1.06 MHz, and −0.43 to −0.26 MHz for foF2 and in ranges from 0.701 to 0.8, 22.39 to 28.45 km, and −9.28 to 11.06 km for hmF2.
Landslide Displacement Prediction via Attentive Graph Neural Network
Authors: Kuang Ping , Li Rongfan , Huang Ying , Wu Jin , Luo Xucheng , Zhou Fan
Published: April 2022

Landslides are among the most common geological hazards that result in considerable human and economic losses globally. Researchers have put great efforts into addressing the landslide prediction problem for decades. Previous methods either focus on analyzing the landslide inventory maps obtained from aerial photography and satellite images or propose machine learning models—trained on historical land deformation data—to predict future displacement and sedimentation. However, existing approaches generally fail to capture complex spatial deformations and their inter-dependencies in different areas. This work presents a novel landslide prediction model based on graph neural networks, which utilizes graph convolutions to aggregate spatial correlations among different monitored locations. Besides, we introduce a novel locally historical transformer network to capture dynamic spatio-temporal relations and predict the surface deformation. We conduct extensive experiments on real-world data and demonstrate that our model significantly outperforms state-of-the-art approaches in terms of prediction accuracy and model interpretations.
Low-SNR Doppler Data Processing for the InSight Radio Science Experiment
Authors: Buccino Dustin , Border James S. , Folkner William M. , Kahan Daniel , Le Maistre Sebastien
Published: April 2022

Radio Doppler measurements between the InSight lander and NASA’s Deep Space Network have been acquired for measuring the rotation of Mars. Unlike previous landers used for this purpose that utilized steerable high-gain antennas, InSight uses two fixed medium-gain antennas, which results in a lower radio signal-to-noise ratio (SNR). Lower SNR results in additional thermal noise for Doppler measurements using standard processes. Through a combination of phase averaging and traditional data compression, the increased thermal noise due to low SNR can be removed for most of the signal of interest, resulting in more accurate Doppler measurements. During the first 900 days of InSight operations, Doppler measurements were improved by ~25% on average using this method.
Global Identification of Unelectrified Built-Up Areas by Remote Sensing
Authors: Gao Xumiao , Wu Mingquan , Niu Zheng , Chen Fang
Published: April 2022

Access to electricity (the proportion of the population with access to electricity) is a key indica for of the United Nations’ Sustainable Development Goal 7 (SDG7), which aims to provide affordable, reliable, sustainable, and modern energy services for all. Accurate and timely global data on access to electricity in all countries is important for the achievement of SDG7. Current survey-based access to electricity datasets suffers from short time spans, slow updates, high acquisition costs, and a lack of location data. Accordingly, a new method for identifying the electrification status of built-up areas based on the remote sensing of nighttime light is proposed in this study. More specifically, the method overlays global built-up area data with night-time light remote sensing data to determine whether built-up areas are electrified based on a threshold night-time light value. By using our approach, electrified and unelectrified built-up areas were extracted at 500 m resolution on a global scale for the years 2014 and 2020. The acquired results show a significant reduction in an unelectrified built-up area between 2014 and 2020, from 51,301.14 km2 to 22,192.52 km2, or from 3.05% to 1.32% of the total built-up area. Compared to 2014, 117 countries or territories had improved access to electricity, and 18 increased their proportion of unelectrified built-up area by >0.1%. The identification accuracy was evaluated by using a random sample of 10,106 points. The accuracies in 2014 and 2020 were 97.29% and 98.9%, respectively, with an average of 98.1%. The outcomes of this method are in high agreement with the spatial distribution of access to electricity data reported by the World Bank. This study is the first to investigate the global electrification of built-up areas by using remote sensing. It makes an important supplement to global data on access to electricity, which can aid in the achievement of SDG7.
GA-Net-Pyramid: An Efficient End-to-End Network for Dense Matching
Authors: Xia Yuanxin , d’Angelo Pablo , Fraundorfer Friedrich , Tian Jiaojiao , Fuentes Reyes Mario , Reinartz Peter
Published: April 2022

Dense matching plays a crucial role in computer vision and remote sensing, to rapidly provide stereo products using inexpensive hardware. Along with the development of deep learning, the Guided Aggregation Network (GA-Net) achieves state-of-the-art performance via the proposed Semi-Global Guided Aggregation layers and reduces the use of costly 3D convolutional layers. To solve the problem of GA-Net requiring large GPU memory consumption, we design a pyramid architecture to modify the model. Starting from a downsampled stereo input, the disparity is estimated and continuously refined through the pyramid levels. Thus, the disparity search is only applied for a small size of stereo pair and then confined within a short residual range for minor correction, leading to highly reduced memory usage and runtime. Tests on close-range, aerial, and satellite data demonstrate that the proposed algorithm achieves significantly higher efficiency (around eight times faster consuming only 20–40% GPU memory) and comparable results with GA-Net on remote sensing data. Thanks to this coarse-to-fine estimation, we successfully process remote sensing datasets with very large disparity ranges, which could not be processed with GA-Net due to GPU memory limitations.
Predicting Landslides Susceptible Zones in the Lesser Himalayas by Ensemble of Per Pixel and Object-Based Models
Authors: Sur Ujjwal , Singh Prafull , Meena Sansar Raj , Singh Trilok Nath
Published: April 2022

Landslide susceptibility is a contemporary method for delineation of landslide hazard zones and holistically mitigating the future landslides risks for planning and decision-making. The significance of this study is that it would be the first instance when the ‘geon’ model will be attempted to delineate landslide susceptibility map (LSM) for the complex lesser Himalayan topography as a contemporary LSM technique. This study adopted the per-pixel-based ensemble approaches through modified frequency ratio (MFR) and fuzzy analytical hierarchy process (FAHP) and compared it with the ‘geons’ (object-based) aggregation method to produce an LSM for the lesser Himalayan Kalsi-Chakrata road corridor. For the landslide susceptibility models, 14 landslide conditioning factors were carefully chosen; namely, slope, slope aspect, elevation, lithology, rainfall, seismicity, normalized differential vegetation index, stream power index, land use/land cover, soil, topographical wetness index, and proximity to drainage, road, and fault. The inventory data for the past landslides were derived from preceding satellite images, intensive field surveys, and validation surveys. These inventory data were divided into training and test datasets following the commonly accepted 70:30 ratio. The GIS-based statistical techniques were adopted to establish the correlation between landslide training sites and conditioning factors. To determine the accuracy of the model output, the LSMs accuracy was validated through statistical methods of receiver operating characteristics (ROC) and relative landslide density index (R-index). The accuracy results indicate that the object-based geon methods produced higher accuracy (geon FAHP: 0.934; geon MFR: 0.910) over the per-pixel approaches (FAHP: 0.887; MFR: 0.841). The results noticeably showed that the geon method constructs significant regional units for future mitigation strategies and development. The present study may significantly benefit the decision-makers and regional planners in selecting the appropriate risk mitigation procedures at a local scale to counter the potential damages and losses from landslides in the area.
A Lightweight System-On-Chip Based Cryptographic Core for Low-Cost Devices
Authors: Gookyi Dennis Agyemanh Nana , Ryoo Kwangki
Published: April 2022

The backbone of the Internet of things (IoT) platform consists of tiny low-cost devices that are continuously exchanging data. These devices are usually limited in terms of hardware footprint, memory capacity, and processing power. The devices are usually insecure because implementing standard cryptographic algorithms requires the use of a large hardware footprint which leads to an increase in the prices of devices. This study implements a System-on-Chip (SoC) based lightweight cryptographic core that consists of two encryption protocols, four authentication protocols, and a key generation/exchange protocol for ultra-low-cost devices. The hardware architectures use the concept of resource sharing to minimize the hardware area. The lightweight cryptographic SoC is tested by designing a desktop software application to serve as an interface to the hardware. The design is implemented using Verilog HDL and the 130 nm CMOS cell library is used for synthesis, which results in 33 k gate equivalents at a maximum clock frequency of 50 MHz.
An Ultra-High-Resolution Bending Temperature Decoupled Measurement Sensor Based on a Novel Core Refractive Index-like Linear Distribution Doped Fiber
Authors: Zhang Yunshan , Zhang Yulin , Hu Xiafen , Wu Dan , Fan Li , Wang Zhaokui , Kong Linxing
Published: April 2022

A high-resolution and high-sensitivity fiber optic sensor based on the quasi-linear distribution of the core refractive index is designed and fabricated, which enables decouple measurement of bending and of temperature. First, single-mode fiber doped with Al2O3, Y2O3, and P2O5 was drawn through a fiber drawing tower. The fiber grating was engraved on the fiber by a femtosecond laser. Modeling analysis was conducted from quantum theory. Experimental results show that the bending sensitivity of the grating can reach 21.85 dB/m−1, which is larger than the reported sensitivity of similar sensors. In the high temperature range from room temperature to 1000 °C, the temperature sensitivity was 14.1 pm/°C. The doped grating sensor can achieve high temperature measurement without annealing, and it has a distinguished linear response from low temperature to high temperature. The bending resolution can reach 0.0004 m−1, and the temperature resolution can reach 0.007 °C. Two-parameter decoupling measurement can be realized according to the distinctive characteristic trends of the spectrum. What’s more, the sensor exhibits excellent stability and a fast response time.
A New Optical Configuration for the Surface Encoder with an Expanded Z-Directional Measuring Range
Authors: Hong Yifan , Sato Ryo , Shimizu Yuki , Matsukuma Hiraku , Gao Wei
Published: April 2022

This paper proposes a new optical configuration for a two-axis surface encoder that can measure the in-plane (X-axis) and out-of-plane (Z-axis) displacements of a positioning stage. The two-axis surface encoder is composed of a scale grating and a sensor head. A transparent grating is employed in the sensor head for measurement of the Z-directional displacement of the scale grating based on the Fizeau-type measurement method; a reference beam reflected from the transparent grating and the zeroth-order diffracted beam from the scale grating are superimposed to generate an interference signal. A pair of prisms and a beam splitter are also employed in the sensor head, so that the positive and negative first-order diffracted beams can be superimposed over a long working distance to generate an interference signal for measurement of the X-directional displacement of the scale grating. Focusing on the new, extended Z-directional measurement mechanism, proof-of-principle experiments were carried out to verify the feasibility of the proposed optical configuration for the surface encoder that can measure the uni-directional displacements of a scale grating along the X- and Z-axis. Experimental results from the developed optical configuration demonstrated the achievement of a Z-directional measuring range of ±1.5 mm.
External Load Analysis in Beach Handball Using a Local Positioning System and Inertial Measurement Units
Authors: Müller Carsten , Willberg Christina , Reichert Lukas , Zentgraf Karen
Published: April 2022

Beach handball is a young discipline that is characterized by numerous high-intensity actions. By following up on previous work, the objective was to perform in-depth analyses evaluating external load (e.g., distance traveled, velocity, changes in direction, etc.) in beach handball players. In cross-sectional analyses, data of 69 players belonging to the German national or prospective team were analyzed during official tournaments using a local positioning system (10 Hz) and inertial measurement units (100 Hz). Statistical analyses comprised the comparison of the first and second set and the effects of age and sex (female adolescents vs. male adolescents vs. male adults) and playing position (goalkeepers, defenders, wings, specialists, and pivots) on external load measures. We found evidence for reduced external workload during the second set of the matches (p = 0.005, ηp2 = 0.09), as indicated by a significantly lower player load per minute and number of changes in direction. Age/sex (p < 0.001, ηp2 = 0.22) and playing position (p < 0.001, ηp2 = 0.29) also had significant effects on external load. The present data comprehensively describe and analyze important external load measures in a sample of high-performing beach handball players, providing valuable information to practitioners and coaches aiming at improving athletic performance in this new sport.
Active Disturbance Rejection Control in Magnetic Bearing Rotor Systems with Redundant Structures
Authors: Cheng Baixin , Cheng Xin , Song Shao , Wu Huachun , Hu Yefa , Zhou Rougang , Deng Shuai
Published: April 2022

At present, magnetic bearings are a better energy-saving choice than mechanical bearings in industrial applications. However, there are strongly coupled characteristics in magnetic bearing–rotor systems with redundant structures, and uncertain disturbances in the electrical system as well as external disturbances, and these unfavorable factors degrade the performance of the system. To improve the anti-interference performance of magnetic bearing systems, this paper proposes the inverse of the current distribution matrix W−1 meaning that the active disturbance rejection control simulation model can be carried out without neglecting the current of each coil. Firstly, based on the working mechanism of magnetic bearings with redundant structures and the nonlinear electromagnetic force model, the current and displacement stiffness models of magnetic bearings are established, and a dynamic model of the rotor is constructed. Then, according to the dynamic model of the rotor and the mapping relationship between the current of each coil and the electromagnetic force of the magnetic bearing, we established the equivalent control loop of the magnetic bearing–rotor system with redundant structures. Finally, on the basis of the active disturbance rejection control (ADRC) strategy, we designed a linear active disturbance rejection controller (LADRC) for magnetic bearings with redundant structures under the condition of no coil failure, and a corresponding simulation was carried out. The results demonstrate that compared to PID+current distribution control strategy, the LADRC+current distribution control strategy proposed in this paper is able to effectively improve the anti-interference performance of the rotors supported by magnetic bearings with redundant structures.
Location and Time Aware Multitask Allocation in Mobile Crowd-Sensing Based on Genetic Algorithm
Authors: Ipaye Aridegbe A. , Chen Zhigang , Asim Muhammad , Chelloug Samia Allaoua , Guo Lin , Ibrahim Ali M. A. , Abd El-Latif Ahmed A.
Published: April 2022

Mobile crowd-sensing (MCS) is a well-known paradigm used for obtaining sensed data by using sensors found in smart devices. With the rise of more sensing tasks and workers in the MCS system, it is now essential to design an efficient approach for task allocation. Moreover, to ensure the completion of the tasks, it is necessary to incentivise the workers by rewarding them for participating in performing the sensing tasks. In this paper, we aim to assist workers in selecting multiple tasks while considering the time constraint of the worker and the requirements of the task. Furthermore, a pricing mechanism is adopted to determine each task budget, which is then used to determine the payment for the workers based on their willingness factor. This paper proves that the task-allocation is a non-deterministic polynomial (NP)-complete problem, which is difficult to solve by conventional optimization techniques. A worker multitask allocation-genetic algorithm (WMTA-GA) is proposed to solve this problem to maximize the workers welfare. Finally, theoretical analysis demonstrates the effectiveness of the proposed WMTA-GA. We observed that it performs better than the state-of-the-art algorithms in terms of average performance, workers welfare, and the number of assigned tasks.
A Real-Time Detection Device for the Rapid Quantification of Skin Casual Sebum Using the Oil Red O Staining Method
Authors: Ahn Kung , Han Sangjin , Yun Kyeongeui , Lee Wooseok , Lee Dong-Geol , Kang So Min , Choi Young-Bong , Han Kyudong , Ahn Yong Ju
Published: April 2022

The human skin sebum suggests that it (along with other epidermal surface lipids) plays a role in skin barrier formation, the moderation of cutaneous inflammation, and antimicrobial defense. Various methods have been developed for collecting and measuring skin sebum. We tested methods of detection using “color intensity”, by staining the skin casual sebum. This process was conducted in three steps; first, the selection of materials for sebum collection; second, staining the collected sebum; third, the development of a device that can measure the level of stained sebum. A plastic film was used to effectively collect sebum that increased with the replacement time of the sebum. In addition, the collected sebum was stained with Oil Red O (ORO) and checked with RGB; as a result, the R2 value was higher than 0.9. It was also confirmed that the correlation value was higher than 0.9 in the comparison result with Sebumeter®, which is a common standard technology. Finally, it was confirmed that the R2 value was higher than 0.9 in the detection value using the sensor. In conclusion, we have proven the proof of concept (PoC) for this method, and we would like to introduce an effective sebum measurement method that differs from the existing method.
Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey
Authors: Hurtado Sánchez Johanna Andrea , Casilimas Katherine , Caicedo Rendon Oscar Mauricio
Published: April 2022

Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving 5G and 6G networks. A 5G/6G network can comprise various network slices from unique or multiple tenants. Network providers need to perform intelligent and efficient resource management to offer slices that meet the quality of service and quality of experience requirements of 5G/6G use cases. Resource management is far from being a straightforward task. This task demands complex and dynamic mechanisms to control admission and allocate, schedule, and orchestrate resources. Intelligent and effective resource management needs to predict the services’ demand coming from tenants (each tenant with multiple network slice requests) and achieve autonomous behavior of slices. This paper identifies the relevant phases for resource management in network slicing and analyzes approaches using reinforcement learning (RL) and DRL algorithms for realizing each phase autonomously. We analyze the approaches according to the optimization objective, the network focus (core, radio access, edge, and end-to-end network), the space of states, the space of actions, the algorithms, the structure of deep neural networks, the exploration–exploitation method, and the use cases (or vertical applications). We also provide research directions related to RL/DRL-based network slice resource management.