bluuebunny/crossref_metadata_2025 huggingface dataset:
Nanostructured Lipid Carrier Gel Formulation of Recombinant Human Thrombomodulin Improve Diabetic Wound Healing by Topical Administration
Authors: Hsueh Yuan-Shuo , Shyong Yan-Jye , Yu Hsiu-Ching , Jheng Shu-Jhen , Lin Shang-Wen , Wu Hua-Lin , Tsai Jui-Chen
Published: September 2021

Recombinant human thrombomodulin (rhTM), an angiogenesis factor, has been demonstrated to stimulate cell proliferation, keratinocyte migration and wound healing. The objective of this study was to develop nanostructured lipid carrier (NLC) formulations encapsulating rhTM for promoting chronic wound healing. RhTM-loaded NLCs were prepared and characterized. Encapsulation efficiency was more than 92%. The rate of rhTM release from different NLC formulations was influenced by their lipid compositions and was sustained for more than 72 h. Studies on diabetic mouse wound model suggested that rhTM-NLC 1.2 µg accelerated wound healing and was similar to recombinant human epidermal growth factor-NLC (rhEGF-NLC) 20 µg. By incorporating 0.085% carbopol (a highly crosslinked polyacrylic acid polymer) into rhTM NLC, the NLC-gel presented similar particle characteristics, and demonstrated physical stability, sustained release property and stability within 12 weeks. Both rhTM NLC and rhTM NLC-gel improved wound healing of diabetic mice and cell migration of human epidermal keratinocyte cell line (HaCaT) significantly. In comparison with rhTM solution, plasma concentrations of rhTM post applications of NLC and NLC-gel formulations were lower and more sustained in 24 h. The developed rhTM NLC and rhTM NLC-gel formulations are easy to prepare, stable and convenient to apply to the wound with reduced systemic exposure, which may warrant potential delivery systems for the care of chronic wound patients.
Novel Ex Vivo Zymography Approach for Assessment of Protease Activity in Tissues with Activatable Antibodies
Authors: Howng Bruce , Winter Michael B. , LePage Carol , Popova Irina , Krimm Michael , Vasiljeva Olga
Published: September 2021

Proteases are involved in the control of numerous physiological processes, and their dysregulation has been identified in a wide range of pathologies, including cancer. Protease activity is normally tightly regulated post-translationally and therefore cannot be accurately estimated based on mRNA or protein expression alone. While several types of zymography approaches to estimate protease activity exist, there remains a need for a robust and reliable technique to measure protease activity in biological tissues. We present a novel quantitative ex vivo zymography (QZ) technology based on Probody® therapeutics (Pb-Tx), a novel class of protease-activated cancer therapeutics that contain a substrate linker cleavable by tumor-associated proteases. This approach enables the measurement and comparison of protease activity in biological tissues via the detection of Pb-Tx activation. By exploiting substrate specificity and selectivity, cataloguing and differentiating protease activities is possible, with further refinement achieved using protease-specific inhibitors. Using the QZ assay and human tumor xenografts, patient tumor tissues, and patient plasma, we characterized protease activity in preclinical and clinical samples. The QZ assay offers the potential to increase our understanding of protease activity in tissues and inform diagnostic and therapeutic development for diseases, such as cancer, that are characterized by dysregulated proteolysis.
Proteomics-Based Retinal Target Engagement Analysis and Retina-Targeted Delivery of 17β-Estradiol by the DHED Prodrug for Ocular Neurotherapy in Males
Authors: Prokai-Tatrai Katalin , Zaman Khadiza , Nguyen Vien , De La Cruz Daniel L. , Prokai Laszlo
Published: September 2021

We examined the impact of 17β-estradiol (E2) eye drops on the modulation of the proteome profile in the male rat retina. With discovery-driven proteomics, we have identified proteins that were regulated by our treatment. These proteins were assembled to several bioinformatics-based networks implicating E2’s beneficial effects on the male rat retina in a broad context of ocular neuroprotection including the maintenance of retinal homeostasis, facilitation of efficient disposal of damaged proteins, and mitochondrial respiratory chain biogenesis. We have also shown for the first time that the hormone’s beneficial effects on the male retina can be constrained to this target site by treatment with the bioprecursor prodrug, DHED. A large concentration of E2 was produced after DHED eye drops not only in male rat retinae but also in those of rabbits. However, DHED treatment did not increase circulating E2 levels, thereby ensuring therapeutic safety in males. Targeted proteomics focusing on selected biomarkers of E2’s target engagement further confirmed the prodrug’s metabolism to E2 in the male retina and indicated that the retinal impact of DHED treatment was identical to that of the direct E2 treatment. Altogether, our study shows the potential of topical DHED therapy for an efficacious and safe protection of the male retina without the unwanted hormonal side-effects associated with current estrogen therapies.
Antimicrobial Polymer-Based Hydrogels for the Intravaginal Therapies—Engineering Considerations
Authors: Gosecka Monika , Gosecki Mateusz
Published: September 2021

The review is focused on the hydrogel systems dedicated to the intravaginal delivery of antibacterial, antifungal and anti-Trichomonas vaginalis activity drugs for the treatment of gynaecological infections. The strategies for the enhancement of the hydrophobic drug solubility in the hydrogel matrix based on the formation of bigel systems and the introduction of nano- and microparticles as a drug reservoir are presented. Hydrogel carriers of natural and synthetic pharmacological substances, drug-free systems displaying antimicrobial activity thanks to the hydrogel building elements and systems combining the antimicrobial activity of both drug and polymer building components are distinguished. The design of hydrogels facilitating their administration and proper distribution in the vaginal mucosa and the vagina based on thermoresponsive systems capable of gelling at vaginal conditions and already-cross-linked injectable systems after reaching the yield stress are discussed. In addition, the mechanisms of hydrogel bioadhesion that regulate the retention time in the vagina are indicated. Finally, the prospects for the further development of hydrogel-based drug carriers in gynaecological therapies are highlighted.
Fabrication of 2 kW-Level Chirped and Tilted Fiber Bragg Gratings and Mitigating Stimulated Raman Scattering in Long-Distance Delivery of High-Power Fiber Laser
Authors: Zhao Xiaofan , Tian Xin , Wang Meng , Rao Binyu , Li Hongye , Xi Xiaoming , Wang Zefeng
Published: September 2021

Chirped and tilted fiber Bragg gratings (CTFBGs) have attracted a lot of attention in stimulated Raman scattering (SRS) suppression of high-power fiber lasers. However, the laser power handling capacity seriously limits their applications. In this paper, by optimizing the inscription parameters and post-processing strategy, we fabricate a large-mode-area double-cladding CTFBG with a thermal slope of ~0.015 °C/W due to the low insertion loss of about 0.15 dB, which make it possible for direct kilowatt-level application. A 2 kW-level fiber laser oscillator is employed to test the CTFBG, and a series of experiments have been carried out to compare the effect of SRS mitigation in high-power fiber laser long-distance delivery. In addition, the influence of CTFBGs on laser beam quality is studied for the first time. Experimental results indicated that the CTFBG could effectively mitigate SRS and has no obvious influence on laser beam quality. This work opens a new opportunity for further power scaling and the delivery of high-power fiber lasers over longer distances.
All-Fiber Gas Cavity Based on Anti-Resonant Hollow-Core Fibers Fabricated by Splicing with End Caps
Authors: Shi Jing , Ye Xinyu , Cui Yulong , Huang Wei , Li Hao , Zhou Zhiyue , Wang Meng , Chen Zilun , Wang Zefeng
Published: September 2021

In recent years, fiber gas lasers have obtained a rapid development, however, efficient and stable pump coupling is a key limitation for their applications in the future. Here, we report an all-fiber gas cavity based on anti-resonant hollow-core fibers which have the beneficial properties of adjustable broad transmission bands and potential low transmission attenuation, especially in the mid-infrared. This kind of all-fiber gas cavity is fabricated by directly splicing with end caps at both ends for the first time. The high-power laser transmission characteristics were studied, and the experimental results show that the all-fiber gas cavities have a very stable performance. The maximum input laser power at 1080 nm is about 260 W, and the output power is 203 W, giving a total transmission efficiency of 78.1%. This work opens a new opportunity for the development of high-power all-fiber structured fiber gas lasers.
Frontiers in the Standardization of the Plant Platform for High Scale Production of Vaccines
Authors: Citiulo Francesco , Crosatti Cristina , Cattivelli Luigi , Biselli Chiara
Published: September 2021

The recent COVID-19 pandemic has highlighted the value of technologies that allow a fast setup and production of biopharmaceuticals in emergency situations. The plant factory system can provide a fast response to epidemics/pandemics. Thanks to their scalability and genome plasticity, plants represent advantageous platforms to produce vaccines. Plant systems imply less complicated production processes and quality controls with respect to mammalian and bacterial cells. The expression of vaccines in plants is based on transient or stable transformation systems and the recent progresses in genome editing techniques, based on the CRISPR/Cas method, allow the manipulation of DNA in an efficient, fast, and easy way by introducing specific modifications in specific sites of a genome. Nonetheless, CRISPR/Cas is far away from being fully exploited for vaccine expression in plants. In this review, an overview of the potential conjugation of the renewed vaccine technologies (i.e., virus-like particles—VLPs, and industrialization of the production process) with genome editing to produce vaccines in plants is reported, illustrating the potential advantages in the standardization of the plant platforms, with the overtaking of constancy of large-scale production challenges, facilitating regulatory requirements and expediting the release and commercialization of the vaccine products of genome edited plants.
Wet-Spun Composite Filaments from Lignocellulose Nanofibrils/Alginate and Their Physico-Mechanical Properties
Authors: Park Ji-Soo , Han Song-Yi , Bandi Rajkumar , Lee Eun-Ah , Cindradewi Azelia-Wulan , Kim Jeong-Ki , Kwon Gu-Joong , Seo Young-Ho , Youe Won-Jae , Gwon Jaegyoung , Park Chan-Woo , Lee Seung-Hwan
Published: September 2021

Lignocellulose nanofibrils (LCNFs) with different lignin contents were prepared using choline chloride (ChCl)/lactic acid (LA), deep eutectic solvent (DES) pretreatment, and subsequent mechanical defibrillation. The LCNFs had a diameter of 15.3–18.2 nm, which was similar to the diameter of commercial pure cellulose nanofibrils (PCNFs). The LCNFs and PCNFs were wet-spun in CaCl2 solution for filament fabrication. The addition of sodium alginate (AL) significantly improved the wet-spinnability of the LCNFs. As the AL content increased, the average diameter of the composite filaments increased, and the orientation index decreased. The increase in AL content improved the wet-spinnability of CNFs but deteriorated the tensile properties. The increase in the spinning rate resulted in an increase in the orientation index, which improved the tensile strength and elastic modulus.
Rheological and Mechanical Properties of Resin-Based Materials Applied in Dental Restorations
Authors: Zhang Xinyuan , Zhang Qi , Meng Xin , Ye Yuting , Feng Daoshuo , Xue Jing , Wang Hanbing , Huang Haofei , Wang Ming , Wang Jing
Published: September 2021

Resin-based materials have been prevalent for dental restorations over the past few decades and have been widely used for a variety of direct and indirect procedures. Typically, resin-based dental materials are required to be flowable or moldable before setting and can provide adequate mechanical strength after setting. The setting method may include, but is not limited to, light-curing, self-curing or heating. In this review, based on different indications of resin-based dental materials (e.g., dental filling composite, dental bonding agent, resin luting cement), their rheological and mechanical properties were reviewed. Viscous and flexible properties were focused on for materials before setting, while elastic properties and mechanical strength were focused on for materials after setting. At the same time, the factors that may affect their rheological and mechanical properties were discussed. It is anticipated that the insightful information and prospections of this study will be useful to the future development and fabrication of resin-based dental restorative materials.
Functional Adhesion of Pectin Biopolymers to the Lung Visceral Pleura
Authors: Zheng Yifan , Pierce Aidan F. , Wagner Willi L. , Khalil Hassan A. , Chen Zi , Servais Andrew B. , Ackermann Maximilian , Mentzer Steven J.
Published: September 2021

Pleural injuries and the associated “air leak” are the most common complications after pulmonary surgery. Air leaks are the primary reason for prolonged chest tube use and increased hospital length of stay. Pectin, a plant-derived heteropolysaccharide, has been shown to be an air-tight sealant of pulmonary air leaks. Here, we investigate the morphologic and mechanical properties of pectin adhesion to the visceral pleural surface of the lung. After the application of high-methoxyl citrus pectin films to the murine lung, we used scanning electron microscopy to demonstrate intimate binding to the lung surface. To quantitatively assess pectin adhesion to the pleural surface, we used a custom adhesion test with force, distance, and time recordings. These assays demonstrated that pectin–glycocalyceal tensile adhesive strength was greater than nanocellulose fiber films or pressure-sensitive adhesives (p < 0.001). Simultaneous videomicroscopy recordings demonstrated that pectin–glycocalyceal adhesion was also stronger than the submesothelial connective tissue as avulsed surface remnants were visualized on the separated pectin films. Finally, pleural abrasion and hyaluronidase enzyme digestion confirmed that pectin binding was dependent on the pleural glycocalyx (p < 0.001). The results indicate that high methoxyl citrus pectin is a promising sealant for the treatment of pleural lung injuries.
Preparation and Application of Fluorine-Free Finishing Agent with Excellent Water Repellency for Cotton Fabric
Authors: Yu Chengbing , Shi Kaiqin , Ning Jinyan , Zheng Zhe , Yu Hualong , Yang Zhenxuan , Liu Jun
Published: September 2021

Water repellent is an important functional finish for cotton fabric. However, cotton fabrics often have poor washing resistance and other performances after actual finishing. In this study, based on the structural characteristics of cotton fiber and durability of water repellent, a cross-linked amino long-chain alkyl polysiloxane (CAHPS) was first prepared, and then reacted with modified silica. Finally, a chemically bonded organic–inorganic nanohybrid cross-linked polysiloxane (rSiO2–CAHPS) was fabricated. Furthermore, the rSiO2–CAHPS was emulsified to obtain a durable fluorine-free water repellent. The water repellent finishing for cotton fabric was carried out by the pad–dry–cure process. After finishing, the cotton fabric had good resistance to conventional liquids and excellent washing resistance, and still maintained good water repellency after 30 rounds of soaping. Moreover, properties including air permeability, mechanical property and whiteness are hardly affected after finishing. SEM and XPS characterization show that a layer of dense silicon film is formed on the surface of cotton fabric by rSiO2–CAHPS water repellent. The existence of nanosilica can improve the surface roughness of cotton fibers. The synergistic effect of fiber matrix, nanoparticles and CAHPS endows the fabric with a micro/nano-multi-scale micro-rough structure, which improves the water repellency of cotton fabric after water repellent finishing.
Improving Mechanical Properties of PLA/Starch Blends Using Masterbatch Containing Vegetable Oil Based Active Ingredients
Authors: Nagy Bianka , Miskolczi Norbert , Eller Zoltán
Published: September 2021

The aim of this research was to increase the compatibility between PLA and starch with vegetable oil-based additives. Based on tensile results, it can be stated, that Charpy impact strength could be improved for 70/30 and 60/40 blends in both unconditioned and conditioned cases, regardless of vegetable oil, while no advantageous change in impact strength was obtained with PLA-g-MA. Considering sample with the highest starch concentration (50%), the flexural modulus was improved by using sunflower oil-based additive, Charpy impact strength and elongation at break was increased using rapeseed oil-based additive in both conditioned and unconditioned cases. SEM images confirmed the improvement of compatibility between components.
Estimating the Methane Potential of Energy Crops: An Overview on Types of Data Sources and Their Limitations
Authors: Zhang Yue , Kusch-Brandt Sigrid , Salter Andrew M. , Heaven Sonia
Published: September 2021

As the anaerobic digestion of energy crops and crop residues becomes more widely applied for bioenergy production, planners and operators of biogas plants, and farmers who consider growing such crops, have a need for information on potential biogas and methane yields. A rich body of literature reports methane yields for a variety of such materials. These data have been obtained with different testing methods. This work elaborates an overview on the types of data source available and the methods that are commonly applied to determine the methane yield of an agricultural biomass, with a focus on European crops. Limitations regarding the transferability and generalisation of data are explored, and crop methane values presented across the literature are compared. Large variations were found for reported values, which can only partially be explained by the methods applied. Most notably, the intra-crop variation of methane yield (reported values for a single crop type) was higher than the inter-crop variation (variation between different crops). The pronounced differences in reported methane yields indicate that relying on results from individual assays of candidate materials is a high-risk approach for planning biogas operations, and the ranges of values such as those presented here are essential to provide a robust basis for estimation.
Computational Fluid Dynamics Modelling of Liquid–Solid Slurry Flows in Pipelines: State-of-the-Art and Future Perspectives
Authors: Messa Gianandrea Vittorio , Yang Qi , Adedeji Oluwaseun Ezekiel , Chára Zdeněk , Duarte Carlos Antonio Ribeiro , Matoušek Václav , Rasteiro Maria Graça , Sanders R. Sean , Silva Rui C. , de Souza Francisco José
Published: September 2021

Slurry pipe transport has directed the efforts of researchers for decades, not only for the practical impact of this problem, but also for the challenges in understanding and modelling the complex phenomena involved. The increase in computer power and the diffusion of multipurpose codes based on Computational Fluid Dynamics (CFD) have opened up the opportunity to gather information on slurry pipe flows at the local level, in contrast with the traditional approaches of simplified theoretical modelling which are mainly based on a macroscopic description of the flow. This review paper discusses the potential of CFD for simulating slurry pipe flows. A comprehensive description of the modelling methods will be presented, followed by an overview of significant publications on the topic. However, the main focus will be the assessment of the potential and the challenges of the CFD approach, underlying the essential interplay between CFD simulations and experiments, discussing the main sources of uncertainty of CFD models, and evaluating existing models based on their interpretative or predictive capacity. This work aims at providing a solid ground for students, academics, and professional engineers dealing with slurry pipe transport, but it will also provide a methodological approach that goes beyond the specific application.
Problems of Selected Sectors of Biofuels for Transport in Poland
Authors: Borowski Piotr F. , Kupczyk Adam , Biernat Krzysztof , Mączyńska-Sęczek Joanna , Detka Tomasz , Golisz Ewa , Gawłowska Agnieszka , Di Nardo Mario
Published: September 2021

The paper discusses issues related to the sectors of biofuels for transport. Development directions of those sectors and factors limiting the growth rate thereof are analysed. At present, researchers’ attention is increasingly focused on development of the alternative fuels sector. Moreover, issues related to waste used in the sector of alternative fuels are now among the leading undertakings of environmental engineering. The authors have analysed the potential of biofuels sectors in Poland taking into account the EU’s legislative requirements. The paper contains a discussion of the sector of esters, liquid biofuels, sector of lignocellulose, sector of liquid bio-hydrocarbons and, additionally, pays attention to the sector of electromobility as one of the most attractive and prospective sectors in terms of emission reduction.
Demand Forecasting for Multichannel Fashion Retailers by Integrating Clustering and Machine Learning Algorithms
Authors: Chen I-Fei , Lu Chi-Jie
Published: September 2021

In today’s rapidly changing and highly competitive industrial environment, a new and emerging business model—fast fashion—has started a revolution in the apparel industry. Due to the lack of historical data, constantly changing fashion trends, and product demand uncertainty, accurate demand forecasting is an important and challenging task in the fashion industry. This study integrates k-means clustering (KM), extreme learning machines (ELMs), and support vector regression (SVR) to construct cluster-based KM-ELM and KM-SVR models for demand forecasting in the fashion industry using empirical demand data of physical and virtual channels of a case company to examine the applicability of proposed forecasting models. The research results showed that both the KM-ELM and KM-SVR models are superior to the simple ELM and SVR models. They have higher prediction accuracy, indicating that the integration of clustering analysis can help improve predictions. In addition, the KM-ELM model produces satisfactory results when performing demand forecasting on retailers both with and without physical stores. Compared with other prediction models, it can be the most suitable demand forecasting method for the fashion industry.
Formation Control of Swarming Vessels Using a Virtual Matrix Approach and ISOT Guidance Algorithm
Authors: Kim Su-Rim , Jo Hyun-Jae , Kim Jung-Hyeon , Park Jong-Yong
Published: September 2021

The formation control for the effective operation of multiple vessels is discussed. First, a virtual matrix approach is proposed to improve the formation robustness and transform performance during swarm operations, which is created based on the virtual leader vessel location, and agents composing the formation follow cells in the matrix to maintain formation. This approach is affected by the virtual leader vessel location. The virtual leader vessel location is defined by two cases: matrix center and geometric center; furthermore, robustness and efficiency comparison simulations are performed. The simulation results show that in most formations, the geometric center is better in terms of efficiency and robustness. Second, the isosceles triangle guidance algorithm is proposed to improve the “go-back behavior” of certain agents during excessive maneuvering. Through a waypoint-following simulation, the algorithm is confirmed to be superior to the line-of-sight guidance algorithm. The swarm simulation on the virtual map verifies the performance of the proposed formation control and guidance algorithm.
Nanocellulose from Agricultural Wastes: Products and Applications—A Review
Authors: Mateo Soledad , Peinado Silvia , Morillas-Gutiérrez Francisca , La Rubia M. Dolores , Moya Alberto J.
Published: September 2021

The isolation of nanocellulose from different agricultural residues is becoming an important research field due to its versatile applications. This work collects different production processes, including conditioning steps, pretreatments, bleaching processes and finally purification for the production of nanocellulose in its main types of morphologies: cellulose nanofiber (CNF) and cellulose nanocrystal (CNC). This review highlights the importance of agricultural wastes in the production of nanocellulose in order to reduce environmental impact, use of fossil resources, guarantee sustainable economic growth and close the circle of resource use. Finally, the possible applications of the nanocellulose obtained as a new source of raw material in various industrial fields are discussed.
The Economics of Fruit and Vegetable Production Irrigated with Reclaimed Water Incorporating the Hidden Costs of Life Cycle Environmental Impacts
Authors: Canaj Kledja , Mehmeti Andi , Berbel Julio
Published: September 2021

The estimation and quantification of external environmental costs (hidden costs) are crucial to sustainability assessments of treated wastewater reuse projects. These costs, however, are rarely considered in economic analysis studies. In this work, monetized life cycle assessment (LCA) and life cycle costing (LCC) were combined into a hybrid model to calculate cradle-to-farm gate external environmental costs (EEC) and internal costs (IC) of producing 1 t of plant-based product irrigated with reclaimed water in a Mediterranean context. The total cost was calculated by combining monetized LCA and LCC results. The results for the crops under consideration were 119.4 €/t for tomatoes, 344.4 €/t for table grapes, and 557 €/t for artichokes. Our findings show that there are significant hidden costs at the farm level, with EEC accounting for 57%, 23%, and 38% of the total cost of tomatoes, table grapes, and artichokes, respectively. Electricity use for water treatment and fertilization generated most of the EEC driven by the global warming, particulate matter, acidification, and fossil resource scarcity impact categories. When compared to groundwater, the higher internal costs of reclaimed water were offset by lower external costs, particularly when supported by low-energy wastewater treatment. This demonstrates that incorporating EEC into economic analyses might generate a better understanding of the profitability of treated wastewater reuse in crop production. In Italy and the Mediterranean region, research on the sustainability of water reuse in irrigation through life cycle thinking is still limited. Using a multi-metric approach, our analysis brought new insights into both economic and environmental performance – and their tradeoff relationships in wastewater reuse for irrigation of agricultural crops. In future research, it would be of interest to use different monetization methods as well as to investigate social externalities to explore their size and role in the total external costs.
Cross-Domain Scene Classification Based on a Spatial Generalized Neural Architecture Search for High Spatial Resolution Remote Sensing Images
Authors: Chen Yuling , Teng Wentao , Li Zhen , Zhu Qiqi , Guan Qingfeng
Published: September 2021

By labelling high spatial resolution (HSR) images with specific semantic classes according to geographical properties, scene classification has been proven to be an effective method for HSR remote sensing image semantic interpretation. Deep learning is widely applied in HSR remote sensing scene classification. Most of the scene classification methods based on deep learning assume that the training datasets and the test datasets come from the same datasets or obey similar feature distributions. However, in practical application scenarios, it is difficult to guarantee this assumption. For new datasets, it is time-consuming and labor-intensive to repeat data annotation and network design. The neural architecture search (NAS) can automate the process of redesigning the baseline network. However, traditional NAS lacks the generalization ability to different settings and tasks. In this paper, a novel neural network search architecture framework—the spatial generalization neural architecture search (SGNAS) framework—is proposed. This model applies the NAS of spatial generalization to cross-domain scene classification of HSR images to bridge the domain gap. The proposed SGNAS can automatically search the architecture suitable for HSR image scene classification and possesses network design principles similar to the manually designed networks. To obtain a simple and low-dimensional search space, the traditional NAS search space was optimized and the human-the-loop method was used. To extend the optimized search space to different tasks, the search space was generalized. The experimental results demonstrate that the network searched by the SGNAS framework with good generalization ability displays its effectiveness for cross-domain scene classification of HSR images, both in accuracy and time efficiency.
Estimating the Gross Primary Production and Evapotranspiration of Rice Paddy Fields in the Sub-Tropical Region of China Using a Remotely-Sensed Based Water-Carbon Coupled Model
Authors: Gan Guojing , Zhao Xiaosong , Fan Xingwang , Xie Henwang , Jin Weirong , Zhou Han , Cui Yifan , Liu Yuanbo
Published: September 2021

Rice serves as the staple food for over 50% of the global population. Remotely-sensed based estimation of the gross primary production (GPP) and evapotranspiration (ET) of rice paddy fields is essential to assess global food security. In this study, we tested the application of a recently proposed remotely-sensed based water-carbon coupled model (PML-V2) in the lower reaches of the Poyang Lake plain, which is one of the nine production bases for crops in China. Evaluation using the eddy covariance measurements showed that, after parameter localization, the model reproduced the seasonal variations of GPP and ET for both the early rice and the late rice. The model performed reasonably well in the validation period because the key parameters (e.g., the quantum efficiency and the stomatal conductance coefficient) exhibited predictable seasonal variations. At the regional scale, the spatial distribution in multi-year GPP of rice (1365 ± 326 gCm−2year−1) can be explained by the vegetation cover fraction (R2 > 0.9); in comparison, the multi-year ET (1003 ± 65 mm/year) exhibits smaller spatial variations due to the high evaporation rate of the saturated soil surface of paddy fields. The water use efficiency of rice in this region varies around 1.35 gC/kgH2O with a standard deviation of 0.30. Our study shows that GPP and ET of rice can be estimated by remote sensing models without detailed crop management information, which is usually unavailable at regional scales.
Performance of Camera-Based Vibration Monitoring Systems in Input-Output Modal Identification Using Shaker Excitation
Authors: Kalybek Maksat , Bocian Mateusz , Pakos Wojciech , Grosel Jacek , Nikitas Nikolaos
Published: September 2021

Despite significant advances in the development of high-resolution digital cameras in the last couple of decades, their potential remains largely unexplored in the context of input-output modal identification. However, these remote sensors could greatly improve the efficacy of experimental dynamic characterisation of civil engineering structures. To this end, this study provides early evidence of the applicability of camera-based vibration monitoring systems in classical experimental modal analysis using an electromechanical shaker. A pseudo-random and sine chirp excitation is applied to a scaled model of a cable-stayed bridge at varying levels of intensity. The performance of vibration monitoring systems, consisting of a consumer-grade digital camera and two image processing algorithms, is analysed relative to that of a system based on accelerometry. A full set of modal parameters is considered in this process, including modal frequency, damping, mass and mode shapes. It is shown that the camera-based vibration monitoring systems can provide high accuracy results, although their effective application requires consideration of a number of issues related to the sensitivity, nature of the excitation force, and signal and image processing. Based on these findings, suggestions for best practice are provided to aid in the implementation of camera-based vibration monitoring systems in experimental modal analysis.
Validation of AVHRR Land Surface Temperature with MODIS and In Situ LST—A TIMELINE Thematic Processor
Authors: Reiners Philipp , Asam Sarah , Frey Corinne , Holzwarth Stefanie , Bachmann Martin , Sobrino Jose , Göttsche Frank-M. , Bendix Jörg , Kuenzer Claudia
Published: September 2021

Land Surface Temperature (LST) is an important parameter for tracing the impact of changing climatic conditions on our environment. Describing the interface between long- and shortwave radiation fluxes, as well as between turbulent heat fluxes and the ground heat flux, LST plays a crucial role in the global heat balance. Satellite-derived LST is an indispensable tool for monitoring these changes consistently over large areas and for long time periods. Data from the AVHRR (Advanced Very High-Resolution Radiometer) sensors have been available since the early 1980s. In the TIMELINE project, LST is derived for the entire operating period of AVHRR sensors over Europe at a 1 km spatial resolution. In this study, we present the validation results for the TIMELINE AVHRR daytime LST. The validation approach consists of an assessment of the temporal consistency of the AVHRR LST time series, an inter-comparison between AVHRR LST and in situ LST, and a comparison of the AVHRR LST product with concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) LST. The results indicate the successful derivation of stable LST time series from multi-decadal AVHRR data. The validation results were investigated regarding different LST, TCWV and VA, as well as land cover classes. The comparisons between the TIMELINE LST product and the reference datasets show seasonal and land cover-related patterns. The LST level was found to be the most determinative factor of the error. On average, an absolute deviation of the AVHRR LST by 1.83 K from in situ LST, as well as a difference of 2.34 K from the MODIS product, was observed.
A Study of Sea Surface Rain Identification Based on HY-2A Scatterometer
Authors: Peng Yihuan , Xie Xuetong , Lin Mingsen , Ran Lishan , Yuan Feng , Zhou Yuan , Tang Ling
Published: September 2021

Rain affects the wind measurement accuracy of the Ku-band spaceborne scatterometer. In order to improve the quality of the retrieved wind field, it is necessary to identify and flag rain-contaminated data. In this study, an HY-2A scatterometer is used to study rain identification. In addition to the conventional parameters, such as the retrieved wind speed, the wind direction relative to the along-track direction, and the normalized beam difference, the experiment expands the mean deviation of the backscattering coefficient, the beam difference between fore and aft, and the node number of the wind vector cell (WVC) as the sensitive parameters according to the microwave scattering characteristics of rain and the actual measurement situation of the HY-2A. Furthermore, a rain identification model for HY2 (HY2RRM) with the K-Nearest Neighborhood (KNN) algorithm was built. After several tests, the accuracy of the selected HY2RRM approach is found to about 88%, and about 70% of rain-contaminated data can be accurately identified. The research results are helpful for better understanding the characteristics of microwave backscattering and provide a possible way to further improve the wind field retrieval accuracy of the HY-2A scatterometer and other Ku-band scatterometers.
Axle Configuration and Weight Sensing for Moving Vehicles on Bridges Based on the Clustering and Gradient Method
Authors: He Wei , Liang Xiaodong , Deng Lu , Kong Xuan , Xie Hong
Published: September 2021

Traffic information, including vehicle weight and axle spacing, is vital for bridge safety. The bridge weigh-in-motion (BWIM) system remotely estimates the axle weights of moving vehicles using the response measured from instrumented bridges. It has been proved more accurate and durable than the traditional pavement-based method. However, the main drawback of conventional BWIM algorithms is that they can only identify the axle weight and the information of axle configuration (the number of axles and axle spacing) is required to be determined using an extra device in advance of the weight identification procedure. Namely, dedicated sensors (pressure-sensitive sensors placed on the deck surface or under the soffit of a bridge) in addition to weighing sensors must be adopted for identifying the axle configuration, which significantly decreases the utility, feasibility, and economic efficiency of BWIM technology. In this study, a new iterative procedure simultaneously identifying axle spacing as well as axle weights and gross weights of vehicles is proposed. The novel method is based on k-means clustering and the gradient descent method. In this method, both the axle weight and the axle location are obtained by using the same global response of bridges; thus the axle detectors are no longer required, which makes it economical and easier to be implemented. Furthermore, the proposed optimization method has good computational efficiency and thus is practical for real-time application. Comprehensive numerical simulations and laboratory experiments based on scaled vehicle and bridge models were conducted to verify the proposed method. The identification results show that the proposed method has good accuracy and high computational efficiency in axle spacing and axle weight identification.
Implication between Geophysical Events and the Variation of Seasonal Signal Determined in GNSS Position Time Series
Authors: Nistor Sorin , Suba Norbert-Szabolcs , El-Mowafy Ahmed , Apollo Michal , Malkin Zinovy , Nastase Eduard Ilie , Kudrys Jacek , Maciuk Kamil
Published: September 2021

The seasonal signal determined by the Global Navigation Satellite System (GNSS), which is captured in the coordinate time series, exhibits annual and semi-annual periods. This signal is frequently modelled by two periodic signals with constant amplitude and phase-lag. The purpose of this study is to explore the implication of different types of geophysical events on the seasonal signal in three stages—in the time span that contains the geophysical events, before and after the geophysical event, but also the stationarity phenomena, which is analysed on approximately 200 reference stations from the EPN network since 1995. The novelty of the article is demonstrated by correlating three different types of geophysical events, such as earthquakes with a magnitude greater than 6° on the Richter scale, landslides, and volcanic activity, and analysing the variation in amplitude of the seasonal signal. The geophysical events situated within a radius of 30 km from the epicentre showed a higher seasonal value than when the timespan did not contain a geophysical event. The presence of flicker and random walk noise was computed using overlapping Hadamard variance (OHVAR) and the non-stationary behaviour of the time series of the CORS coordinates in the time frequency analysis was done using continuous wavelet transform (CWT).
On-Board Volcanic Eruption Detection through CNNs and Satellite Multispectral Imagery
Authors: Del Rosso Maria Pia , Sebastianelli Alessandro , Spiller Dario , Mathieu Pierre Philippe , Ullo Silvia Liberata
Published: September 2021

In recent years, the growth of Machine Learning (ML) algorithms has raised the number of studies including their applicability in a variety of different scenarios. Among all, one of the hardest ones is the aerospace, due to its peculiar physical requirements. In this context, a feasibility study, with a prototype of an on board Artificial Intelligence (AI) model, and realistic testing equipment and scenario are presented in this work. As a case study, the detection of volcanic eruptions has been investigated with the objective to swiftly produce alerts and allow immediate interventions. Two Convolutional Neural Networks (CNNs) have been designed and realized from scratch, showing how to efficiently implement them for identifying the eruptions and at the same time adapting their complexity in order to fit on board requirements. The CNNs are then tested with experimental hardware, by means of a drone with a paylod composed of a generic processing unit (Raspberry PI), an AI processing unit (Movidius stick) and a camera. The hardware employed to build the prototype is low-cost, easy to found and to use. Moreover, the dataset has been published on GitHub, made available to everyone. The results are promising and encouraging toward the employment of the proposed system in future missions, given that ESA has already moved the first steps of AI on board with the Phisat-1 satellite, launched on September 2020.
Spatiotemporal Monitoring of Soil CO2 Efflux in a Subtropical Forest during the Dry Season Based on Field Observations and Remote Sensing Imagery
Authors: Chen Tao , Xu Zhenwu , Tang Guoping , Chen Xiaohua , Fang Hong , Guo Hao , Yuan Ye , Zheng Guoxiong , Jiang Liangliang , Niu Xiangyu
Published: September 2021

The CO2 efflux from forest soil (FCO2) is one of the largest components of the global carbon cycle. Accurate estimation of FCO2 can help us better understand the carbon cycle in forested areas and precisely predict future climate change. However, the scarcity of field-measured FCO2 data in the subtropical forested area greatly limits our understanding of FCO2 dynamics at regional and global scales. This study used an automatic cavity ring-down spectrophotometer (CRDS) analyzer to measure FCO2 in a typical subtropical forest of southern China in the dry season. We found that the measured FCO2 at two experimental areas experienced similar temporal trends in the dry season and reached the minima around December, whereas the mean FCO2 differed apparently across the two areas (9.05 vs. 5.03 g C m−2 day−1) during the dry season. Moreover, we found that both abiotic (soil temperature and moisture) and biotic (vegetation productivity) factors are significantly and positively correlated, respectively, with the FCO2 variation during the study period. Furthermore, a machine-learning random forest model (RF model) that incorporates remote sensing data is developed and used to predict the FCO2 pattern in the subtropical forest, and the topographic effects on spatiotemporal patterns of FCO2 were further investigated. The model evaluation indicated that the proposed model illustrated high prediction accuracy for the training and testing dataset. Based on the proposed model, the spatiotemporal patterns of FCO2 in the forested watershed that encloses the two monitoring sites were mapped. Results showed that the spatial distribution of FCO2 is obviously affected by topography: the high FCO2 values mainly occur in relatively high altitudinal areas, in slopes of 10–25°, and in sunny slopes. The results emphasized that future studies should consider topographical effects when simulating FCO2 in subtropical forests. Overall, our study unraveled the spatiotemporal variations of FCO2 and their driving factors in a subtropical forest of southern China in the dry season, and demonstrated that the proposed RF model in combination with remote sensing data can be a useful tool for predicting FCO2 in forested areas, particularly in subtropical and tropical forest ecosystems.
Influence of Indian Summer Monsoon on Tropopause, Trace Gases and Aerosols in Asian Summer Monsoon Anticyclone Observed by COSMIC, MLS and CALIPSO
Authors: Basha Ghouse , Ratnam Madineni Venkat , Jiang Jonathan H. , Kishore Pangaluru , Ravindra Babu Saginela
Published: September 2021

The existence of the Asian Summer Monsoon Anticyclone (ASMA) during the summer in the northern hemisphere, upper troposphere and lower stratosphere (UTLS) region plays a significant role in confining the trace gases and aerosols for a long duration, thus affecting regional and global climate. Though several studies have been carried out, our understanding of the trace gases and aerosols variability in the ASMA is limited during different phases of the Indian monsoon. This work quantifies the role of Indian Summer Monsoon (ISM) activity on the tropopause, trace gases (Water Vapor (WV), Ozone (O3), Carbon Monoxide (CO)) and aerosols (Attenuated Scattering Ratio (ASR)) obtained from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC), Microwave Limb Sounder (MLS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite observations, respectively, during the period 2006–2016. Enhancement in the tropopause altitude, WV, CO, ASR and low tropopause temperatures, O3 in the ASMA region is clearly noticed during peak monsoon months (July and August) with large inter-annual variability. Further, a significant increase in the WV and CO, and decrease in O3 during the active phase of the ISM, strong monsoon years and strong La Niña years in the ASMA is noticed. An enhancement in the ASR values during the strong monsoon years and strong La Niña years is also observed. In addition, our results showed that the presence of deep convection spreading from India land regions to the Bay of Bengal with strong updrafts can transport the trace gases and aerosols to the upper troposphere during active spells, strong monsoon years and La Niña years when compared to their counterparts. Observations show that the ASMA is very sensitive to active spells, strong monsoon years and La Niña years compared to break spells, weak monsoon years and El Niño years. It is concluded that the dynamics play a significant role in constraining several trace gases and aerosols in the ASMA and suggested considering the activity of the summer monsoon while dealing with them at sub-seasonal scales.