bluuebunny/crossref_metadata_2025 huggingface dataset:
Innovation in Aircraft Cabin Interior Panels. Part II: Technical Assessment on Replacing Glass Fiber with Thermoplastic Polymers and Panels Fabricated Using Vacuum Forming Process
Authors: Franco-Urquiza Edgar Adrián , Alcántara Llanas Perla Itzel , Rentería-Rodríguez Victoria , Saleme Raúl Samir , Ramírez Aguilar Rodrigo , Zarate Pérez Cecilia , Torres-Arellano Mauricio , Piedra Saúl
Published: September 2021

The manufacturing process of the aircraft cabin interior panels is expensive and time-consuming, and the resulting panel requires rework due to damages that occurred during their fabrication. The aircraft interior panels must meet structural requirements; hence sandwich composites of a honeycomb core covered with two layers of pre-impregnated fiberglass skin are used. Flat sandwich composites are transformed into panels with complex shapes or geometries using the compression molding process, leading to advanced manufacturing challenges. Some aircraft interior panels are required for non-structural applications; hence sandwich composites can be substituted by cheaper alternative materials and transformed using disruptive manufacturing techniques. This paper evaluates the feasibility of replacing the honeycomb and fiberglass skin layers core with rigid polyurethane foams and thermoplastic polymers. The results show that the structural composites have higher mechanical performances than the proposed sandwich composites, but they are compatible with non-structural applications. Sandwich composite fabrication using the vacuum forming process is feasible for developing non-structural panels. This manufacturing technique is fast, easy, economical, and ecological as it uses recyclable materials. The vacuum forming also covers the entire panel, thus eliminating tapestries, paints, or finishes to the aircraft interior panels. The conclusion of the article describes the focus of future research.
Structural Design Calculation of Basalt Fiber Polymer-Modified RPC Beams Subjected to Four-Point Bending
Authors: Gong Yafeng , Yang Jianxing , He Xin , Lyu Xiang , Liu Hanbing
Published: September 2021

In this paper, a basalt fiber surface was treated with coupling agent KH-550 and hydrochloric acid, and the basalt fiber polymer-modified active powder concrete (RPC) material was prepared. There are significant differences in material composition and properties between basalt fiber polymer-modified RPC and ordinary concrete, and the structural design calculation (cracking moment and normal section bending bearing capacity) of an ordinary reinforced concrete beam is no longer applicable. Thus, mechanical parameters such as displacement and strain of reinforcement basalt fiber polymer-modified RPC beams subjected to four-point bending were tested. The excellent compressive and tensile strengths of basalt fiber polymer-modified RPC were fully utilized. The tensile strength of basalt fiber polymer-modified RPC in the tensile zone of the beam was considered in the calculation of normal section bending bearing capacity of reinforcement basalt fiber polymer-modified RPC beams. The results showed that the measured values of the cracking moment and ultimate failure bending moment of reinforcement basalt fiber polymer-modified RPC beams were in good agreement with the calculated values. The established formulas for cracking moment and normal section bending bearing capacity can provide references for the design of reinforcement basalt fiber polymer-modified RPC simply supported beam and promote the wide application of basalt fiber polymer-modified RPC materials in practical engineering.
Preparation of Polyurethane Adhesives from Crude and Purified Liquefied Wood Sawdust
Authors: Jiang Wen , Hosseinpourpia Reza , Biziks Vladimirs , Ahmed Sheikh Ali , Militz Holger , Adamopoulos Stergios
Published: September 2021

Polyurethane (PU) adhesives were prepared with bio-polyols obtained via acid-catalyzed polyhydric alcohol liquefaction of wood sawdust and polymeric diphenylmethane diisocyanate (pMDI). Two polyols, i.e., crude and purified liquefied wood (CLW and PLW), were obtained from the liquefaction process with a high yield of 99.7%. PU adhesives, namely CLWPU and PLWPU, were then prepared by reaction of CLW or PLW with pMDI at various isocyanate to hydroxyl group (NCO:OH) molar ratios of 0.5:1, 1:1, 1.5:1, and 2:1. The chemical structure and thermal behavior of the bio-polyols and the cured PU adhesives were analyzed by Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). Performance of the adhesives was evaluated by single-lap joint shear tests according to EN 302-1:2003, and by adhesive penetration. The highest shear strength was found at the NCO:OH molar ratio of 1.5:1 as 4.82 ± 1.01 N/mm2 and 4.80 ± 0.49 N/mm2 for CLWPU and PLWPU, respectively. The chemical structure and thermal properties of the cured CLWPU and PLWPU adhesives were considerably influenced by the NCO:OH molar ratio.
Skin-like Transparent Polymer-Hydrogel Hybrid Pressure Sensor with Pyramid Microstructures
Authors: Kang Kyumin , Jung Hyunjin , An Soojung , Baac Hyoung Won , Shin Mikyung , Son Donghee
Published: September 2021

Soft biomimetic electronic devices primarily comprise an electronic skin (e-skin) capable of implementing various wearable/implantable applications such as soft human–machine interfaces, epidermal healthcare systems, and neuroprosthetics owing to its high mechanical flexibility, tissue conformability, and multifunctionality. The conformal contact of the e-skin with living tissues enables more precise analyses of physiological signals, even in the long term, as compared to rigid electronic devices. In this regard, e-skin can be considered as a promising formfactor for developing highly sensitive and transparent pressure sensors. Specifically, to minimize the modulus mismatch at the biotic–abiotic interface, transparent-conductive hydrogels have been used as electrodes with exceptional pressing durability. However, critical issues such as dehydration and low compatibility with elastomers remain a challenge. In this paper, we propose a skin-like transparent polymer-hydrogel hybrid pressure sensor (HPS) with microstructures based on the polyacrylamide/sodium-alginate hydrogel and p-PVDF-HFP-DBP polymer. The encapsulated HPS achieves conformal contact with skin due to its intrinsically stretchable, highly transparent, widely sensitive, and anti-dehydrative properties. We believe that the HPS is a promising candidate for a robust transparent epidermal stretchable-skin device.
Investigation on the α/δ Crystal Transition of Poly(l-lactic Acid) with Different Molecular Weights
Authors: Zhang Lei , Zhao Guoqun , Wang Guilong
Published: September 2021

Poly(l-lactic acid) (PLLA) crystal possesses a complex polymorphism, and the formation mechanism of various crystal forms has been a hot research topic in the field of polymer condensate matter. In this research, five kinds of PLLA with different molecular weights were prepared by ring-opening polymerization with strict dehydration operations and multistep purification treatments. Then, thin film isothermal crystallization experiments were carried out to obtain crystallized samples. Previous research has proven that the PLLA α crystal form is usually formed at a temperature above 120 °C and the PLLA δ (or α’) crystal form is usually formed at a temperature below 120 °C. However, in this research, the characterization results indicated that the PLLA crystal changed from δ form to α form with the decrease of molecular weight at a temperature of 80 °C. Considering the molecular weight effect, the paper argued that the transitions of the α/δ crystal form are not only associated with temperature, but also related to entanglement state before crystallization. The small-angle X-ray scattering of the PLLA crystal and rheology analysis of the PLLA melt before crystallization further proved the significant role of entanglement. Finally, we tentatively proposed the entanglement effect mechanism on the transitions of the α/δ crystal form.
Gellan Gum Hydrogels Filled Edible Oil Microemulsion for Biomedical Materials: Phase Diagram, Mechanical Behavior, and In Vivo Studies
Authors: Muktar Muhammad Zulhelmi , Bakar Muhammad Ameerul Amin , Amin Khairul Anuar Mat , Che Rose Laili , Wan Ismail Wan Iryani , Razali Mohd Hasmizam , Abd Razak Saiful Izwan , in het Panhuis Marc
Published: September 2021

The demand for wound care products, especially advanced and active wound care products is huge. In this study, gellan gum (GG) and virgin coconut oil (VCO) were utilized to develop microemulsion-based hydrogel for wound dressing materials. A ternary phase diagram was constructed to obtain an optimized ratio of VCO, water, and surfactant to produce VCO microemulsion. The VCO microemulsion was incorporated into gellan gum (GG) hydrogel (GVCO) and their chemical interaction, mechanical performance, physical properties, and thermal behavior were examined. The stress-at-break (σ) and Young’s modulus (YM) of GVCO hydrogel films were increased along with thermal behavior with the inclusion of VCO microemulsion. The swelling degree of GVCO hydrogel decreased as the VCO microemulsion increased and the water vapor transmission rate of GVCO hydrogels was comparable to commercial dressing in the range of 332–391 g m−2 d−1. The qualitative antibacterial activities do not show any inhibition against Gram-negative (Escherichia coli and Klebsiella pneumoniae) and Gram-positive (Staphylococcus aureus and Bacillus subtilis) bacteria. In vivo studies on Sprague–Dawley rats show the wound contraction of GVCO hydrogel is best (95 ± 2%) after the 14th day compared to a commercial dressing of Smith and Nephew Opsite post-op waterproof dressing, and this result is supported by the ultrasound images of wound skin and histological evaluation of the wound. The findings suggest that GVCO hydrogel has the potential to be developed as a biomedical material.
A Review on Mechanical Models for Cellular Media: Investigation on Material Characterization and Numerical Simulation
Authors: Luo Guoqiang , Zhu Yuxuan , Zhang Ruizhi , Cao Peng , Liu Qiwen , Zhang Jian , Sun Yi , Yuan Huan , Guo Wei , Shen Qiang , Zhang Lianmeng
Published: September 2021

Cellular media materials are used for automobiles, aircrafts, energy-efficient buildings, transportation, and other fields due to their light weight, designability, and good impact resistance. To devise a buffer structure reasonably and avoid resource and economic loss, it is necessary to completely comprehend the constitutive relationship of the buffer structure. This paper introduces the progress on research of the mechanical properties characterization, constitutive equations, and numerical simulation of porous structures. Currently, various methods can be used to construct cellular media mechanical models including simplified phenomenological constitutive models, homogenization algorithm models, single cell models, and multi-cell models. This paper reviews current key mechanical models for cellular media, attempting to track their evolution from their inception to their latest development. These models are categorized in terms of their mechanical modeling methods. This paper focuses on the importance of constitutive relationships and microstructure models in studying mechanical properties and optimizing structural design. The key issues concerning this topic and future directions for research are also discussed.
De-Doped Polyaniline as a Mediating Layer Promoting In-Situ Growth of Metal–Organic Frameworks on Cellulose Fiber and Enhancing Adsorptive-Photocatalytic Removal of Ciprofloxacin
Authors: Hou Xinyu , Sun Lijian , Hu Ying , An Xianhui , Qian Xueren
Published: September 2021

New kinds of inorganic–organic hybrid porous materials, metal–organic frameworks (MOFs), have shown great application potential in various fields, but their powdery nature limits their application to a certain extent. As a green and renewable biomass material in nature, cellulose fiber (CelF) has the advantages of biodegradability, recyclability and easy processing, and can be used as an excellent flexible substrate for MOFs. However, the efficient deposition of MOFs on CelF is still a great challenge for the development of this new material. Herein, polyaniline (PANI) and de-doped PANI (DPANI) with rich functional groups as a mediating layer was proposed to promote the in-situ growth and immobilization of some MOFs on CelF. The PANI (especially DPANI) layer greatly promoted the deposition of the four MOFs, and more encouragingly, significantly promoted the in-situ growth and nanocrystallization of MIL-100(Fe). MIL-100(Fe)@DPANI@CelF was selected as an adsorbent-photocatalyst to be used for the adsorptive-photocatalytic removal of ciprofloxacin (CIP) in water. The removal efficiency of CIP by MIL-100(Fe)@DPANI@CelF reached 82.78%, and the removal capacity of CIP was as high as 105.96 mg g−1. The study found that DPANI had a synergistic effect on both the in-situ growth of MIL-100(Fe) on CelF and the adsorption-photocatalysis of CIP in water. The universal platform of PANI-mediated in-situ growth and immobilization of MOFs on CelF constructed in this study widens the road for the development of MOF@CelF composites.
Advanced Maximum Power Control Algorithm Based on a Hydraulic System for Floating Wave Energy Converters
Authors: Roh Chan , Ha Yoon-Jin , Shin Seungh-Ho , Kim Kyong-Hwan , Park Ji-Yong
Published: September 2021

An integrated analysis is required to evaluate the performance of control algorithms used in power take-off (PTO) systems for floating wave energy converters (FWECs). However, research on PTO systems based on the existing hydraulic device has mainly focused on the input power generation performance rather than on obtaining maximum power through hydraulic device-based electrical load control. The power generation performance is analyzed based on the control variables of the existing torque control algorithm (TCA); however, the amount of power generation for each control variable changes significantly based on the cycle of wave excitation moments. This paper proposes a control algorithm to obtain the maximum power by modeling a hydraulic-device-based integrated FWEC. It also proposes a TCA that can obtain the maximum power regardless of the period of wave excitation moment. The proposed TCA continuously monitors the power generation output and changes the PTO damping coefficient in the direction in which the power generation output can be increased. The proposed TCA increased the output power generation by up to 18% compared to each PTO damping coefficient of the conventional TCA. Thus, the proposed method results in higher power generation regardless of the wave excitation moment cycle and performs better than the existing torque control algorithm.
Photocatalysis for Heavy Metal Treatment: A Review
Authors: Gao Xinyu , Meng Xiangchao
Published: September 2021

Environmental and human health are threatened by anthropogenic heavy metal discharge into watersheds. Traditional processes have many limitations, such as low efficiency, high cost, and by-products. Photocatalysis, an emerging advanced catalytic oxidation technology, uses light energy as the only source of energy. It is a clean new technology that can be widely used in the treatment of organic pollutants in water. Given the excellent adaptability of photocatalysis in environmental remediation, it can be used for the treatment of heavy metals. In this comprehensive review, the existing reported works in relevant areas are summarized and discussed. Moreover, recommendations for future work are provided.
Time-Course Transcriptome Analysis Reveals Global Gene Expression Profiling and Dynamic Developmental Signatures across Complete Life Cycle of Bombyx mori
Authors: Wang Xueqi , Fan Yixuan , Ge Qi , Xu Jia , Taha Rehab Hosny , Yuan Yi , Chen Keping
Published: September 2021

Background: The silkworm (Bombyx mori) is an important lepidopteran model insect worldwide which undergoes a complete metamorphosis developmental process. Although genome sequencing has been long performed, no transcriptome data covering the complete life cycle are available. Methods: Herein, a total of 10 samples were collected consecutively at four different developmental stages, including eggs of 24 h after oviposition (Ed) and eggs of 24 h after artificial egg-hatching (E); larvae from fist to fifth instar (L1–L5); early and late pupa (P4 and P8); and adult moth (M), were subjected to Illumina RNA-Seq and time-course analysis. Results: The summations of the gene expression of the silkworm ten developmental stages show: at Ed stage, eggs develop towards diapause status, the total gene expression level is relatively low; at E stage, after artificial egg-hatching, the expression level improves rapidly; during larval stages from L1–L5, the expression level rises gradually and reaches a peak at L5 stage; during pupae and moth stages, the total gene expression decline stage by stage. The results revealed a dynamical gene expression profile exhibiting significant differential expressions throughout the silkworm life cycle. Moreover, stage-specific key genes were identified at different developmental stages, suggesting their functions mainly characterized in maintaining insect development and immunity homeostasis or driving metamorphosis. GO annotation and KEGG enrichment analysis further revealed the most significantly enriched and fundamentally biological processes during silkworm growth. Conclusion: Collectively, our omics data depicted the first comprehensive landscape of dynamic transcriptome throughout complete developmental processes of B. mori. Our findings also provide valuable references and novel insights into understanding the molecular developmental remodeling events for other Lepidoptera species.
The Impact of Operating Parameters on the Gas-Phase Sulfur Concentration after High Temperature Sulfur Sorption on a Supported Mo-Mn Sorbent
Authors: Ma Jianyu , Mahmoodinia Mehdi , Rout Kumar R. , Blekkan Edd A.
Published: September 2021

The impact of operating parameters on H2S capture from a syngas mixture by a Mo-promoted Mn-based high-temperature sorbent was investigated. The parameters investigated included temperature, space velocity, H2S concentration in the feed gas, and steam content. The H2S and SO2 concentrations in the gas after passing over a bed of the sorbent were analyzed and compared with thermodynamic calculations. The results confirmed that low temperature, low space velocity, low H2S concentration, and a dry feed were favorable for achieving a low residual concentration of sulfur compounds in the effluent gas. The sorbent was able to reduce the residual H2S concentration to below 1 ppm under all tested conditions. However, the unavoidable steam content in the gas phase had a significant adverse effect on sulfur removal from the gas. An empirical model, containing the three variables, i.e., temperature, space velocity, and H2S concentration in the feed, was developed and can be used to predict the effluent H2S residual concentration after treatment by the 15Mn8Mo sorbent.
Multistage Constructed Wetland in the Treatment of Greywater under Tropical Conditions: Performance, Operation, and Maintenance
Authors: Magalhães Filho Fernando J. C. , de Souza Filho José C. M. , Paulo Paula L.
Published: September 2021

Greywater (GW) can be separated in different fractions where the kitchen component might be included. Constructed wetland (CW) systems are commonly used for the onsite treatment of GW, and the fraction treated might impact the performance, operation, and maintenance. These aspects are still poorly explored in the literature and are of importance for a proper design and system sustainability. In this study, a multi-stage household-scale CW system composed of a horizontal flow (HF), followed by a vertical flow (VF) unit, was monitored over 1330 days, focusing on different GW fractions and hydraulic and organic loading rates. The biochemical oxygen demand (BOD) was ~50% lower without the kitchen sink component (GWL) in the system inlet, while no drop was observed in the chemical oxygen demand (COD). Treatment with the GWL component caused a sudden drop in the hydraulic loading rate applied at the HF-CW (~114 to 35 mm per day) and the VF-CW (~230 to 70 mm per day). Even when the HF-CW received ~90 gCOD m−2 per day (GW), the multistage system reached a COD removal of 90%. The lower BOD load when treating GWL avoids clogging and decreases the frequency of maintenance. These variables can be used for the optimal design and operation of a CW, contributing with empirical data to CW guidelines in Brazil, and could additionally be expanded for application in other countries with similar climates.
Islam Is Not Bad, Muslims Are: I’m Done with Islam
Authors: Ainz-Galende Alexandra , Rodríguez-Puertas Rubén
Published: September 2021

The present paper addresses the motives that make some inhabitants of the Spanish province of Granada that converted to Islam leave it after some time. We have approached this reality using grounded theory and conducting nineteen in-depth interviews. Two of the main conclusions are that all interviewees were under great pressure due to the expectations that Muslims they interacted with—partners, family, people from Muslim associations or internet groups, etc.—had of them, and that said expectations were based on interpretations of a fundamentalist nature. Additionally, the fact that these people left Islam makes it evident that their existence is grounded in a ‘self’ under constant construction and open to the possibility of starting to be, continuing to be, or changing depending on their personal choice.
Hinduism, Hindutva and Hindu Populism in India: An Analysis of Party Manifestos of Indian Rightwing Parties
Authors: Saleem Raja M. Ali
Published: September 2021

Since the rise of the Bharatiya Janata Party (BJP), a lot has been written on Hindu nationalism. Prime Minister Modi’s ascendency has similarly resulted in a plethora of books and articles on Hindu populism. However, most of the literature does not distinguish between the two. Hindu nationalism and Hindu populism overlap, particularly in Modi’s India and Modi’s BJP, but they are not the same. In this article, after a discussion on Hinduism’s affinity to populism, an attempt has been made to distinguish between Hindu nationalism and Hindu populism based on an analysis of Hindutva parties’ election manifestos. Since independence, three Hindutva parties have made a name for themselves at the national level: Hindu Mahasabha, Bharatiya Jana Sangh (BJS) and BJP. Based on their importance and success at the national level, one manifesto of Hindu Mahasabha, two manifestos of BJS and four manifestos of the BJP were analyzed based on criteria chosen after literature review. The results show that while Hindu nationalism was strong and visible in early Hindutva parties (Hindu Mahasabha and BJS), Hindu populism was weak and sporadic. Interestingly, for the BJP, there is rise and then drop in Hindu nationalism while Hindu populism has consistently increased.
Trends in Online Religious Processes during the Coronavirus Pandemic in Hungary—Digital Media Use and Generational Differences
Authors: Mónika Andok
Published: September 2021

The present study shows how Hungarian churches and religious communities responded to the physical closure and relocation to online spaces in the spring of 2020, since while physical gates became closed, digital gates became opened. In the churches, work began in two directions with particular intensity. On the one hand, they organized their online appearance. On the other hand, they began to rethink their theological reflections on the possibilities of digital technology. The study also analyses both the event- and community-based presence of the churches as well as what they broadcast to their believers. The intention was to find the answer to what the presence of the camera meant in the process of live broadcasting, with a special focus on the visual elements and procedures that differed from the visual perception of real presence during streaming: the camera movement, the different viewing angles, the location of the cameras, the cut, and the sound quality. In other words, the believers had a new visual experience, an optical representation of reality, which afforded them a new type of interactivity and participation. In addition, the study highlights the generational differences that can be explored in digital transitions.
From the Beehives: Identification and Comparison of Physicochemical Properties of Algerian Honey
Authors: Guerzou Mokhtar , Aouissi Hani Amir , Guerzou Ahlem , Burlakovs Juris , Doumandji Salaheddine , Krauklis Andrey E.
Published: September 2021

In this study, the authors aimed at characterizing 11 Algerian kinds of honey taken from various geographical locations (beehives located at Djelfa (Medjbara and Dzaira), Laghouat, Aflou, Medea, Tiaret, Sidi bel-Abbes, Tiaret, Ain-Safra, Mostaganem, El Bayadh, and Ghardïa). The authors investigated the physicochemical parameters of these honey samples, including density, water content, electrical conductivity, ash content, pH, hydroxymethylfurfural (HMF) content, free acidity, and color. The physicochemical parameters obtained were found to be within acceptable ranges according to the international standards (Codex Alimentarius) for 9 out of 11 analyzed samples: density 1.38–1.50 g/cm3 (the same as kg/L, as commonly used for honey), water content 14.03–18.80%, electrical conductivity 0.38 × 10−1 − 6.41 × 10−1 mS/cm, ash content 0.06–0.48%, pH 3.50–4.50, free acidity 11–47 meq/kg, and color 1.1–9.2 Pfund index. Analysis of HMF content showed that only two honey samples have high values (117.7 and 90.0 meq/kg). Most samples of Algerian honey are of suitable quality according to international standards.
A Robot Architecture Using ContextSLAM to Find Products in Unknown Crowded Retail Environments
Authors: Dworakowski Daniel , Thompson Christopher , Pham-Hung Michael , Nejat Goldie
Published: September 2021

Grocery shoppers must negotiate cluttered, crowded, and complex store layouts containing a vast variety of products to make their intended purchases. This complexity may prevent even experienced shoppers from finding their grocery items, consuming a lot of their time and resulting in monetary loss for the store. To address these issues, we present a generic grocery robot architecture for the autonomous search and localization of products in crowded dynamic unknown grocery store environments using a unique context Simultaneous Localization and Mapping (contextSLAM) method. The contextSLAM method uniquely creates contextually rich maps through the online fusion of optical character recognition and occupancy grid information to locate products and aid in robot localization in an environment. The novelty of our robot architecture is in its ability to intelligently use geometric and contextual information within the context map to direct robot exploration in order to localize products in unknown environments in the presence of dynamic people. Extensive experiments were conducted with a mobile robot to validate the overall architecture and contextSLAM, including in a real grocery store. The results of the experiments showed that our architecture was capable of searching for and localizing all products in various grocery lists in different unknown environments.
Editorial for the Special Issue “New Advances on Sub-Pixel Processing: Unmixing and Mapping Methods”
Authors: Salazar Addisson , Vergara Luis , Safont Gonzalo
Published: September 2021

Innovative remote sensing image processing techniques have been progressively studied due to the increasing availability of remote sensing images, powerful techniques of data analysis, and computational power [...]
MTRC-Tolerated Multi-Target Imaging Based on 3D Hough Transform and Non-Equal Sampling Sparse Solution
Authors: Zou Yimeng , Tian Jiahao , Jin Guanghu , Zhang Yongsheng
Published: September 2021

Distributed radar array brings several new forthcoming advantages in aerospace target detection and imaging. The two-dimensional distributed array avoids the imperfect motion compensation in coherent processing along slow time and can achieve single snapshot 3D imaging. Some difficulties exist in the 3D imaging processing. The first one is that the distributed array may be only in small amount. This means that the sampling does not meet the Nyquist sample theorem. The second one refers to echoes of objects in the same beam that will be mixed together, which makes sparse optimization dictionary too long for it to bring the huge computation burden in the imaging process. In this paper, we propose an innovative method on 3D imaging of the aerospace targets in the wide airspace with sparse radar array. Firstly, the case of multiple targets is not suitable to be processed uniformly in the imaging process. A 3D Hough transform is proposed based on the range profiles plane difference, which can detect and separate the echoes of different targets. Secondly, in the subsequent imaging process, considering the non-uniform sparse sampling of the distributed array in space, the migration through range cell (MTRC)-tolerated imaging method is proposed to process the signal of the two-dimensional sparse array. The uniformized method combining compressed sensing (CS) imaging in the azimuth direction and matched filtering in the range direction can realize the 3D imaging effectively. Before imaging in the azimuth direction, interpolation in the range direction is carried out. The main contributions of the proposed method are: (1) echo separation based on 3D transform avoids the huge amount of computation of direct sparse optimization imaging of three-dimensional data, and ensures the realizability of the algorithm; and (2) uniformized sparse solving imaging is proposed, which can remove the difficulty cause by MTRC. Simulation experiments verified the effectiveness and feasibility of the proposed method.
The Operational Inflight Radiometric Uniform Calibration of a Directional Polarimetric Camera
Authors: Chen Feinan , Luo Donggen , Li Shuang , Yang Benyong , Sun Liang , Ge Shule , Hong Jin
Published: September 2021

The directional polarimetric camera (DPC) on-board the GF-5A satellite is designed for atmospheric or water color detection, which requires high radiometric accuracy. Therefore, in-flight calibration is a prerequisite for its inversion application. For large field optical sensors, it is very challenging to ensure the consistency of radiation detection in the whole field of view in the space environment. Our work proposes a vicarious in-flight calibration method based on sea non-equipment sites (visible bands) and land non-equipment sites (all bands). Combined with environmental parameters and radiation transmission calculations, we evaluated the radiation detection accuracy of the 0° to 60° view zenith angle of the DPC in each band. Our calibration method is based on the single-day normalized radiance data measured by the DPC. Through data selection, enough calibration samples can be obtained in a single day (the number of desert samples is more than 5000, and the number of calibration samples of the ocean is more than 2.8×106). The measurements are compared with the simulation of 6SV VRT code or look-up tables. The massive amount of data averages the uncertainty of a single-point calculation. Although the uncertainty of a single sample is significant, the final fitting of the curve of the variation in the radiometric calibration coefficient with the observation angle can still keep the root mean squared error at approximately 2–3% or even lower, and for visible bands, the calibration results for both ocean sites and desert sites are in good agreement regarding the non-uniformity of the sensor.
Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review
Authors: Neupane Krishna , Baysal-Gurel Fulya
Published: September 2021

Disease diagnosis is one of the major tasks for increasing food production in agriculture. Although precision agriculture (PA) takes less time and provides a more precise application of agricultural activities, the detection of disease using an Unmanned Aerial System (UAS) is a challenging task. Several Unmanned Aerial Vehicles (UAVs) and sensors have been used for this purpose. The UAVs’ platforms and their peripherals have their own limitations in accurately diagnosing plant diseases. Several types of image processing software are available for vignetting and orthorectification. The training and validation of datasets are important characteristics of data analysis. Currently, different algorithms and architectures of machine learning models are used to classify and detect plant diseases. These models help in image segmentation and feature extractions to interpret results. Researchers also use the values of vegetative indices, such as Normalized Difference Vegetative Index (NDVI), Crop Water Stress Index (CWSI), etc., acquired from different multispectral and hyperspectral sensors to fit into the statistical models to deliver results. There are still various drifts in the automatic detection of plant diseases as imaging sensors are limited by their own spectral bandwidth, resolution, background noise of the image, etc. The future of crop health monitoring using UAVs should include a gimble consisting of multiple sensors, large datasets for training and validation, the development of site-specific irradiance systems, and so on. This review briefly highlights the advantages of automatic detection of plant diseases to the growers.
Monitoring Coastline Changes of the Malay Islands Based on Google Earth Engine and Dense Time-Series Remote Sensing Images
Authors: Ding Yaxin , Yang Xiaomei , Jin Hailiang , Wang Zhihua , Liu Yueming , Liu Bin , Zhang Junyao , Liu Xiaoliang , Gao Ku , Meng Dan
Published: September 2021

The use of remote sensing to monitor coastlines with wide distributions and dynamic changes is significant for coastal environmental monitoring and resource management. However, most current remote sensing information extraction of coastlines is based on the instantaneous waterline, which is obtained by single-period imagery. The lack of a unified standard is not conducive to the dynamic change monitoring of a changeable coastline. The tidal range observation correction method can be used to correct coastline observation to a unified climax line, but it is difficult to apply on a large scale because of the distribution of observation sites. Therefore, we proposed a coastline extraction method based on the remote sensing big data platform Google Earth Engine and dense time-series remote sensing images. Through the instantaneous coastline probability calculation system, the coastline information could be extracted without the tidal range observation data to achieve a unified tide level standard. We took the Malay Islands as the experimental area and analyzed the consistency between the extraction results and the existing high-precision coastline thematic products of the same period to achieve authenticity verification. Our results showed that the coastline data deviated 10 m in proportion to a reach of 40% and deviated 50 m within a reach of 89%. The overall accuracy was kept within 100 m. In addition, we extracted 96 additional islands that have not been included in public data. The obtained multi-phase coastlines showed the spatial distribution of the changing hot regions of the Malay Islands’ coastline, which greatly supported our analysis of the reasons for the expansion and retreat of the coastline in this region. These research results showed that the big data platform and intensive time-series method have considerable potential in large-scale monitoring of coastline dynamic change and island reef change monitoring.
Monitoring the Work Cycles of Earthmoving Excavators in Earthmoving Projects Using UAV Remote Sensing
Authors: Wu Yiguang , Wang Meizhen , Liu Xuejun , Wang Ziran , Ma Tianwu , Lu Zhimin , Liu Dan , Xie Yujia , Li Xiuquan , Wang Xing
Published: September 2021

Monitoring the work cycles of earthmoving excavators is an important aspect of construction productivity assessment. Currently, the most advanced method for the recognition of work cycles is the “Stretching-Bending” Sequential Pattern (SBSP), which is based on fixed-carrier video monitoring (FC-SBSP). However, the application of this method presupposes the availability of preconstructed installation carriers to act as a surveillance camera as well as installed and commissioned surveillance systems that work in tandem with them. Obviously, this method is difficult to apply to projects with no conditions for a monitoring camera installation or which have a short construction time. This highlights the potential application of Unmanned Aerial Vehicle (UAV) remote sensing, which is flexible and mobile. Unfortunately, few studies have been conducted on the application of UAV remote sensing for the work cycle monitoring of earthmoving excavators. This research is necessary because the use of UAV remote sensing for monitoring the work cycles of earthmoving excavators can improve construction productivity and save time and costs, especially in post-disaster reconstruction projects involving harsh construction environments, and emergency projects with short construction periods. In addition, the challenges posed by UAV shaking may have to be taken into account when using the SBSP for UAV remote sensing. To this end, this study used application experiments in which stabilization processing of UAV video data was performed for UAV shaking. The application experimental results show that the work cycle performance of UAV remote-sensing-based SBSP (UAV-SBSP) for UAV video data was 2.45% and 5.36% lower in terms of precision and recall, respectively, without stabilization processing than after stabilization processing. Comparative experiments were also designed to investigate the applicability of the SBSP oriented toward UAV remote sensing. Comparative experimental results show that the same level of performance was obtained for the recognition of work cycles with the UAV-SBSP as compared with the FC-SBSP, demonstrating the good applicability of this method. Therefore, the results of this study show that UAV remote sensing enables effective monitoring of earthmoving excavator work cycles in construction sites where monitoring cameras are not available for installation, and it can be used as an alternative technology to fixed-carrier video monitoring for onsite proximity monitoring.
Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World
Authors: Zhang Yongqiang , Ryu Dongryeol , Zheng Donghai
Published: September 2021

Remotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challenge, but with a wide range of research opportunities. The ten contributions in this Special Issue have addressed the following four research topics: (1) Evapotranspiration estimation; (2) rainfall monitoring and prediction; (3) flood simulations and predictions; and (4) monitoring of ecohydrological processes using remote sensing techniques. Moreover, the authors have provided broader discussions, on how to make the most out of the state-of-the-art remote sensing techniques to improve hydrological model simulations and predictions, to enhance their skills in reproducing processes for the fast-changing world.
Airborne SAR Autofocus Based on Blurry Imagery Classification
Authors: Chen Jianlai , Yu Hanwen , Xu Gang , Zhang Junchao , Liang Buge , Yang Degui
Published: September 2021

Existing airborne SAR autofocus methods can be classified as parametric and non-parametric. Generally, non-parametric methods, such as the widely used phase gradient autofocus (PGA) algorithm, are only suitable for scenes with many dominant point targets, while the parametric ones are suitable for all types of scenes, in theory, but their efficiency is generally low. In practice, whether many dominant point targets are present in the scene is usually unknown, so determining what kind of algorithm should be selected is not straightforward. To solve this issue, this article proposes an airborne SAR autofocus approach combined with blurry imagery classification to improve the autofocus efficiency for ensuring autofocus precision. In this approach, we embed the blurry imagery classification based on a typical VGGNet in a deep learning community into the traditional autofocus framework as a preprocessing step before autofocus processing to analyze whether dominant point targets are present in the scene. If many dominant point targets are present in the scene, the non-parametric method is used for autofocus processing. Otherwise, the parametric one is adopted. Therefore, the advantage of the proposed approach is the automatic batch processing of all kinds of airborne measured data.
Improving Ponzi Scheme Contract Detection Using Multi-Channel TextCNN and Transformer
Authors: Chen Yizhou , Dai Heng , Yu Xiao , Hu Wenhua , Xie Zhiwen , Tan Cheng
Published: September 2021

With the development of blockchain technologies, many Ponzi schemes disguise themselves under the veil of smart contracts. The Ponzi scheme contracts cause serious financial losses, which has a bad effect on the blockchain. Existing Ponzi scheme contract detection studies have mainly focused on extracting hand-crafted features and training a machine learning classifier to detect Ponzi scheme contracts. However, the hand-crafted features cannot capture the structural and semantic feature of the source code. Therefore, in this study, we propose a Ponzi scheme contract detection method called MTCformer (Multi-channel Text Convolutional Neural Networks and Transofrmer). In order to reserve the structural information of the source code, the MTCformer first converts the Abstract Syntax Tree (AST) of the smart contract code to the specially formatted code token sequence via the Structure-Based Traversal (SBT) method. Then, the MTCformer uses multi-channel TextCNN (Text Convolutional Neural Networks) to learn local structural and semantic features from the code token sequence. Next, the MTCformer employs the Transformer to capture the long-range dependencies of code tokens. Finally, a fully connected neural network with a cost-sensitive loss function in the MTCformer is used for classification. The experimental results show that the MTCformer is superior to the state-of-the-art methods and its variants in Ponzi scheme contract detection.
Understanding Sexual Agency. Implications for Sexual Health Programming
Authors: Vanwesenbeeck Ine , Cense Marianne , van Reeuwijk Miranda , Westeneng Judith
Published: September 2021

Debates on human agency, especially female and sexual agency, have permeated the social scientific literature and health educational practice for multiple decades now. This article provides a review of recent agency debates illustrating how criticisms of traditional conceptions of (sexual) agency have led to a notable diversification of the concept. A comprehensive, inclusive description of sexual agency is proposed, focusing on the navigation of goals and desires in the wider structural context, and acknowledging the many forms sexual agency may take. We argue there is no simple relation between sexual agency and sexual health. Next, we describe the implications of such an understanding of sexual agency for Comprehensive Sexuality Education (CSE) and for sexual health and rights (SHR) programming more generally. We put forward validation of agentic variety, gender transformative approaches, meaningful youth participation, and multicomponent strategies as essential in building young peoples’ sexual agency and their role as agents of wider societal change. We also show that these essential conditions, wherever they have been studied, are far from being realized. With this review and connected recommendations, we hope to set the stage for ongoing, well-focused research and development in the area.
‘We the People’: Demarcating the Demos in Populist Mobilization—The Case of the Italian Lega
Authors: Schmidtke Oliver
Published: September 2021

This article is a theoretically guided and empirically based analysis of how populist movements invoke the notion of the ‘people’ as a cornerstone of their political mobilization. While the confrontation between the virtuous ‘people’ and the unresponsive elites speaks to how populism challenges established political actors and institutions, the actual meaning of who the ‘people’ are and what they represent is shifting and often driven by strategic considerations. Analytically the article investigates the distinct ways in which nationalism and populism conceptualize and politically mobilize the notion of the ‘people’. Empirically it focuses on the Italian League and engages in a discourse analysis of its political campaigns over the past 30 years. Based on this textual analysis of political campaigns, the article sheds light on how the reference to the ‘people’ has been employed as this political actor has transformed from a regionalist party advocating for autonomy in Northern Italy to one taking up the role of a populist-nationalist party at the national level. This case study allows the author to make a generalizable hypothesis about the nature of identity politics promoted by populist actors and the way in which the invocation of the ‘people’ and their alleged enemies is a pivotal political narrative that opens and restricts opportunities for political mobilization. This interpretative approach also allows for a more concise conceptual understanding of the affinity that right-wing populists demonstrate toward nativist ideologies.
Hybrid Intelligence Strategies for Identifying, Classifying and Analyzing Political Bots
Authors: García-Orosa Berta , Gamallo Pablo , Martín-Rodilla Patricia , Martínez-Castaño Rodrigo
Published: September 2021

Political bots, through astroturfing and other strategies, have become important players in recent elections in several countries. This study aims to provide researchers and the citizenry with the necessary knowledge to design strategies to identify bots and counteract what international organizations have deemed bots’ harmful effects on democracy and, simultaneously, improve automatic detection of them. This study is based on two innovative methodological approaches: (1) dealing with bots using hybrid intelligence (HI), a multidisciplinary perspective that combines artificial intelligence (AI), natural language processing, political science, and communication science, and (2) applying framing theory to political bots. This paper contributes to the literature in the field by (a) applying framing to the analysis of political bots, (b) defining characteristics to identify signs of automation in Spanish, (c) building a Spanish-language bot database, (d) developing a specific classifier for Spanish-language accounts, (e) using HI to detect bots, and (f) developing tools that enable the everyday citizen to identify political bots through framing.