bluuebunny/crossref_metadata_2025 huggingface dataset:
Progress toward Polymerization Reaction Monitoring with Different Dienes: How Small Amounts of Dienes Affect ansa-Zirconocenes/Borate/Triisobutylaluminium Catalyst Systems
Authors: Ali Amjad , Moradian Jamile Mohammadi , Naveed Ahmad , Aziz Tariq , Muhammad Nadeem , Maouche Chanez , Guo Yintian , Yaseen Waleed , Yassen Maria , Haq Fazal , Hassan Mobashar , Fan Zheqing , Guo Li
Published: August 2022

The objectives of this work were to address the fundamental characteristics of ansa-zirconocene catalyzed E/diene copolymerization and E/diene/1-hexene and E/diene/propylene terpolymerizations, and the quantitative relationship between diene structure and polymer chain propagation rate constant in term of quantifiable catalytic active sites. One of the most important but unknown factors in olefins ansa-zirconocene complexes is the distribution of the catalyst between sites actively participating in polymer chain formation and dormant sites. A set of ethylene/dienes copolymerizations, and ethylene/dienes/1-hexene and ethylene/dienes/1-hexene terpolymerizations catalyzed with ansa-zirconocenes/borate/triisobutylaluminium (rac-Et(Ind)2ZrCl2/[Ph3C][B(C6F5)4]/triisobutylaluminium (TIBA) were performed in toluene at 50 °C To determine the active center [C*]/[Zr] ratio variation in the copolymerization of E with different dienes and their terpolymerization with 1-hexene and propylene, each polymer propagation chain ends were quenched with 2-thiophenecarbonyl, which selectively quenches the metal–polymer bonds through acyl chloride. The ethylene, propylene, 1-hexene, and diene composition-based propagation rate constants (kpE, kpP, kp1-H, and kpdiene), thermal (melting and crystalline) properties, composition (mol% of ethylene, propylene, 1-hexene, and diene), molecular weight, and polydispersity were also studied in this work. Systematic comparisons of the proportion of catalytically [Zr]/[C*] active sites and polymerization rate constant (kp) for ansa-zirconocenes catalyzed E/diene, E/diene/1-hexene, and E/diene/propylene polymerization have not been reported before. We evaluated the addition of 1-hexene and propylene as termonomers in the copolymerization with E/diene. To make a comparison for each diene under identical conditions, we started the polymerization by introducing an 80/20 mole ratio of E/P and 0.12 mol/L of 1-hexene in the system. The catalyst behavior against different dienes, 1-hexene, and propylene is very interesting, including changes in thermal properties, cyclization of 1-hexene, and decreased incorporation of isoprene and butadiene, changes in the diffusion barriers in the system, and its effect on kp.
Multi-Scale Modelling of Plastic Deformation, Damage and Relaxation in Epoxy Resins
Authors: Konrad Julian , Pfaller Sebastian , Zahn Dirk
Published: August 2022

Epoxy resin plasticity and damage was studied from molecular dynamic simulations and interpreted by the help of constitutive modelling. For the latter, we suggested a physically motivated approach that aims at interpolating two well-defined limiting cases; namely, pulling at the vanishing strain rate and very rapid deformation; here, taken as 50% of the speed of sound of the material. In turn, to consider 0.1–10-m/s-scale deformation rates, we employed a simple relaxation model featuring exponential stress decay with a relaxation time of 1.5 ns. As benchmarks, deformation and strain reversal runs were performed by molecular dynamic simulations using two different strain rates. Our analyses show the importance of molecular rearrangements within the epoxy network loops for rationalizing the strain-rate dependence of plasticity and residual stress upon strain reversal. To this end, our constitutive model reasonably reproduced experimental data of elastic and visco-elastic epoxy deformation, along with the maximum stress experienced before fracturing. Moreover, we show the importance of introducing damage elements for mimicking the mechanical behavior of epoxy resins.
Strain-Field Modifications in the Surroundings of Impact Damage of Carbon/Epoxy Laminate
Authors: Vlach Jarmil , Doubrava Radek , Růžek Roman , Raška Jan , Horňas Jan , Kadlec Martin
Published: August 2022

The relationship between deformation and stress is crucial for any elasto-plastic body. This paper deals with the experimental identification of the basic parameters of the composite laminate model in relation to the finite element model. Standardized tensile, impact, and post-impact tests on a carbon fiber-reinforced epoxy laminate were used. The method by which the elasticity and failure parameters were obtained from the initial components is described. In the article, the modes of initiation and complete failure of samples in tensile tests, which are compared with the simulation, are presented. Furthermore, the article deals with the issue of the generation and detection of damage by low-speed impact, which can be caused by contact with moving objects, due to improper handling or maintenance. The results of impact analysis simulations are shown in the context of strain-field distribution changes obtained with the help of digital image correlation. The results showed high agreement between the calculations and the experiments. Based on this agreement, simulations of impact damage for various energies were performed. These simulations were used to determine the approximate sizes of the affected zones in relation to the impact energy. The results are finally discussed in the context of the possible use of structural health monitoring based on strain modifications.
The Study of Chemical and Thermal Influences of the Environment on the Degradation of Mechanical Properties of Carbon Composite with Epoxy Resin
Authors: Kojnoková Tatiana , Nový František , Markovičová Lenka
Published: August 2022

The present research deals with the investigation of the influence of aqueous solutions of chemical substances in combination with temperature on the change of material properties of polymer composites based on epoxy resins reinforced with carbon fibers. The aim of the research was to investigate and evaluate the impact of degradation processes due to the influence of chemical environments of different temperatures and time of their action on changes in the material properties and macrostructure of carbon composite with epoxy resin. The chemical and thermal influence of the environment on the experimental material was evaluated by monitoring changes in mechanical properties, glass transition temperature, and material surface macrostructure. The achieved results show different behavior of the experimental composite material in different environments, while it was demonstrated that the degradation effect of chemical and thermal influences on changes in material properties increase with increasing temperature. Among the investigated environments (NaCl, NaOH, and H2SO4), exposure to 10% NaOH, and 15% H2SO4 had the greatest degradation influence on the polymer composite, and exposure to 20% NaCl had the smallest influence, which is also confirmed by invisible changes in material surface macrostructure and decrease of tensile strength by about 20%. Exposure to 10% NaOH resulted in significant surface roughening of the epoxy resin, white deposit creation on the surface, and a decrease of tensile strength by 35%. Opposite that, exposure to 15% H2SO4 resulted in the highlighting of the fiber yarns of the carbon fiber fabric, yellowing of the surface, surface pore occurrence, and a decrease of tensile strength by 35%.
On the Mechanical Properties of Hybrid Dental Materials for CAD/CAM Restorations
Authors: Palacios Teresa , Tarancón Sandra , Pastor José Ygnacio
Published: August 2022

Two hybrid dental materials available for computer-aided design and manufacturing (CAD/CAM) dental restorations have been selected to explore their potential. On the one hand, the scarcely investigated polymer-based material Vita Enamic® (VE) and, on the other hand, the leucite-based material IPS Empress® CAD (EC). Their micro-structure and mechanical performance were analyzed in two environments: directly as received by the manufacturer (AR), and after immersion and storage in artificial saliva (AS) for 30 days to determine the influence of the saliva effect. To avoid an inappropriate selection of materials for clinical use, a full understanding of their mechanical behavior is essential. Therefore, this investigation aims to determine the micro-structural and chemical composition by field emission scanning electron microscopy (FE-SEM) and X-ray fluorescence analysis, establishing the density, micro- and nano-hardness, the nano-elastic modulus, and the flexural strength and fracture toughness (by introducing a femto-laser notch to replicate a real crack). In addition, fracture surfaces of the broken samples were analyzed to correlate the failure micro-mechanisms with their mechanical properties. Results indicate that while the crystalline phase of the materials is very similar (composed of SiO2 and Al2O3), the micro-structure and mechanical behavior is not. The material EC, with finer micro-structure, exhibits a higher mechanical performance but with greater variability of results. Furthermore, the material VE, with a 25 vol.% polymer phase, shows a mechanical performance similar to enamel and dentin and therefore more similar to human behavior.
The Anionic Polymerization of a tert-Butyl-Carboxylate-Activated Aziridine
Authors: Giri Chandan , Chang Jen-Yu , Mbarushimana Pierre Canisius , Rupar Paul A.
Published: August 2022

N-Sulfonyl-activated aziridines are known to undergo anionic-ring-opening polymerizations (AROP) to form polysulfonyllaziridines. However, the post-polymerization deprotection of the sulfonyl groups from polysulfonyllaziridines remains challenging. In this report, the polymerization of tert-butyl aziridine-1-carboxylate (BocAz) is reported. BocAz has an electron-withdrawing tert-butyloxycarbonyl (BOC) group on the aziridine nitrogen. The BOC group activates the aziridine for AROP and allows the synthesis of low-molecular-weight poly(BocAz) chains. A 13C NMR spectroscopic analysis of poly(BocAz) suggested that the polymer is linear. The attainable molecular weight of poly(BocAz) is limited by the poor solubility of poly(BocAz) in AROP-compatible solvents. The deprotection of poly(BocAz) using trifluoroacetic acid (TFA) cleanly produces linear polyethyleneimine. Overall, these results suggest that carbonyl groups, such as BOC, can play a larger role in the in the activation of aziridines in anionic polymerization and in the synthesis of polyimines.
Compaction of a Polymeric Membrane in Ultra-Low-Pressure Water Filtration
Authors: Bilad Muhammad Roil , Junaeda Siti Rahma , Khery Yusran , Nufida Baiq Asma , Shamsuddin Norazanita , Usman Anwar , Violet Violet
Published: August 2022

Applications of ultra-low-pressure filtration systems are increasing as they offer enhanced sustainability due to lower energy input, almost no use of chemicals, and minimum operational expenditure. In many cases, they operate as a decentralized system using a gravity-driven membrane (GDM) filtration process. These applications are relatively new; hence, the fundamental knowledge of the process is still limited. In this study, we investigated the phenomenon of polymeric membrane compaction under an ultra-low-pressure system. The compaction phenomenon is well-recognized in the traditional pressure-driven system operating at high transmembrane pressures (ΔPs > 200 kPa), but it is less documented in ultra-low-pressure systems (ΔP < 10 kPa). A simple GDM filtration setup operated under a constant-pressure system was employed to investigate the compaction phenomena in a polymeric hollow fiber membrane for clean water filtration. Firstly, a short-term pressure stepping test was performed to investigate the occurrence of instantaneous compaction in the ΔP range of 1–10 kPa. The slow compaction was later investigated. Finally, the compaction dynamic was assessed under alternating high and low ΔP and relaxation in between the filtrations. The findings demonstrated the prominence of membrane compaction, as shown by the decreasing trend in clean water permeability at higher ΔPs (i.e., 3240 and 2401 L m−2 h−1 bar−1 at ΔPs of 1 and 10 kPa, respectively). We also found that the intrinsic permeability of the applied polymeric membrane was significantly higher than the apparent one (4351 vs. 2401 L m−2 h−1 bar−1), demonstrating >50% loss due to compaction. The compaction was mainly instantaneous, which occurred when the ΔP was changed, whereas only minor changes in permeability occurred over time when operating at a constant ΔP. The compaction was highly reversible and could be restored (i.e., decompaction) through relaxation by temporarily stopping the filtration. A small fraction of irreversible compaction could be detected by operating alternating filtrations under ΔPs of 1 and 10 kPa. The overall findings are essential to support emerging GDM filtration applications, in which membrane compaction has been ignored and confounded with membrane fouling. The role of compaction is more prominent for high-flux GDM filtration systems treating less-fouling-prone feed (i.e., rainwater, river water) and involving membrane cleaning (i.e., relaxation) in which both reversible and irreversible compaction occurred simultaneously.
Effects of Nanoscale Morphology on Optical Properties of Photoluminescent Polymer Optical Fibers
Authors: Perret Edith , Jakubowski Konrad , Heuberger Manfred , Hufenus Rudolf
Published: August 2022

Bicomponent photoluminescent polymer optical fibers (PL-POFs) have been melt-spun and in-situ drawn to different extents. The results suggest that scattering in the sheath can effectively increase the photoluminescent dye excitation probability in the fiber core. The core/sheath PL-POFs are made of a semi-crystalline fluoropolymer sheath of low refractive index (RI) and an amorphous cycloolefin polymeric core of high RI, which is doped with a luminescent dye. The axial light emission, as well as the guiding attenuation coefficients of the core/sheath PL-POFs, have been measured using a side-illumination set-up. The incident blue laser is down-converted to red light, which is re-emitted and partially guided by the core. The axial light emission is measured at the fiber tip as a function of the distance from the illumination position to the integrating sphere. It is demonstrated that the presence of a semi-crystalline sheath significantly enhances the axial light emission and that it also lowers the attenuation coefficient, compared to the emission and guiding properties of PL core-only fibers. Additionally, the attenuation coefficient has been found to be lower in more strongly drawn PL-POFs. Wide-angle X-ray diffraction and small-angle X-ray scattering experiments reveal structural differences in differently drawn PL-POFs that can be linked to the observed differences in the optical properties.
Fused Deposition Modeling Parameter Optimization for Cost-Effective Metal Part Printing
Authors: Tosto Claudio , Tirillò Jacopo , Sarasini Fabrizio , Sergi Claudia , Cicala Gianluca
Published: August 2022

Metal 3D-printed parts are critical in industries such as biomedical, surgery, and prosthetics to create tailored components for patients, but the costs associated with traditional metal additive manufacturing (AM) techniques are typically prohibitive. To overcome this disadvantage, more cost-effective manufacturing processes are needed, and a good approach is to combine fused deposition modeling (FDM) with debinding-sintering processes. Furthermore, optimizing the printing parameters is required to improve material density and mechanical performance. The design of experiment (DoE) technique was used to evaluate the impact of three printing factors, namely nozzle temperature, layer thickness, and flow rate, on the tensile and bending properties of sintered 316L stainless steel in this study. Green and sintered samples were morphologically and physically characterized after printing, and the optimal printing settings were determined by statistical analysis, which included the surface response technique. The mechanical properties of the specimens increased as the flow rate and layer thickness increased and the nozzle temperature decreased. The optimized printing parameters for the ranges used in this study include 110% flow rate, 140 μm layer thickness, and 240 °C nozzle temperature, which resulted in sintered parts with a tensile strength of 513 MPa and an elongation at break of about 60%.
Challenge and Revolution: An Analysis of Stanislas Julien’s Translation of the Daodejing
Authors: Zhang Can , Xie Pan
Published: August 2022

Retranslation constitutes a special case. as it involves a double creation of values that are determined not only by the ones inscribed in the source text but also by the ones inscribed in the previous translations. Therefore, retranslations initiate dialogues with and even challenges to the previous versions. This paper, rooted in the concept of retranslation, focuses on the first complete published translation of the Daodejing in Europe, the 1842 Lao Tseu Tao Te King: Le Livre de la Voie et de la Vertu, by Stanislas Julien and investigates the revolutionary way Julien interpreted this ancient Chinese classic. Through an analysis of the paratexts and extratexts related to this French version and previous translations, this paper finds that Julien challenged the Christianized and Westernized interpretations of the Daodejing by the European missionaries and sinologists before him and proposed a new system of interpretation: to interpret the Daodejing from the perspective of Laozi and based on the Daoist classics and commentaries. Julien’s translation and interpretations have demonstrated his respect for heterogeneous cultures by acknowledging cultural differences, and he strengthened the authority of his translation by challenging the ideas in previous translations, which makes the retranslation an indispensable reference for the study of Laozi and Daoism.
Quantifying the Long-Term MODIS Cloud Regime Dependent Relationship between Aerosol Optical Depth and Cloud Properties over China
Authors: Li Yanglian , Fan Tianyi , Zhao Chuanfeng , Yang Xin , Zhou Ping , Li Keying
Published: August 2022

Aerosols modify cloud properties and influence the regional climate. The impacts of aerosols on clouds differ for various cloud types, but their long-term relationships have not been fully characterized on a cloud regime basis. In this study, we quantified the cloud regime-dependent relationship between aerosol optical depth (AOD) and cloud properties over China using Moderate-Resolution Imaging Spectroradiometer (MODIS) data from 2002 to 2019. Daily clouds in each 1° by 1° grid were categorized into seven cloud regimes based on the “k-means” clustering algorithm. Overall, the cloud height increased, the cloud thickness and liquid water path increased, and the total cloud cover decreased for all cloud regimes during the study period. Linear correlations between AOD and cloud properties were found within stratocumulus, deep convective, and high cloud regimes, showing consistency with the classic aerosol–cloud interaction paradigms. Using stepwise multivariable linear regression, we found that the meteorological factors dominated the variation of cloud top pressure, while AOD dominated the variation of total cloud cover for most cloud regimes. There are regional differences in the main meteorological factors affecting the cloud properties.
Wide-Area GNSS Corrections for Precise Positioning and Navigation in Agriculture
Authors: Hernández-Pajares Manuel , Olivares-Pulido Germán , Graffigna Victoria , García-Rigo Alberto , Lyu Haixia , Roma-Dollase David , de Lacy M. , Fernández-Prades Carles , Arribas Javier , Majoral Marc , Tisropoulos Zizis , Stamatelopoulos Panagiotis , Symeonidou Machi , Schmidt Michael , Goss Andreas , Erdogan Eren , van Evert Frits , Blok Pieter , Grosso Juan , Spaltro Emiliano , Domínguez Jacobo , López Esther , Hriscu Alina
Published: August 2022

This paper characterizes, with static and roving GNSS receivers in the context of precision agriculture research, the hybrid ionospheric-geodetic GNSS model Wide-Area Real-Time Kinematics (WARTK), which computes and broadcasts real-time corrections for high-precision GNSS positioning and navigation within sparse GNSS receiver networks. This research is motivated by the potential benefits of the low-cost precise WARTK technique on mass-market applications such as precision agriculture. The results from two experiments summarized in this work, the second one involving a working spraying tractor, show, firstly, that the corrections from the model are in good agreement with the corrections provided by IGS (International GNSS Services) analysis centers computed in post-processing from global GNSS data. Moreover, secondly and most importantly, we have shown that WARTK provides navigation solutions at decimeter-level accuracy, and the ionospheric corrections significantly reduce the computational time for ambiguity estimation: up to convergence times for the 50%, 75% and 95% of cases equal or below 30 s (single-epoch), 150 s and 600 s approximately, vs. 1000 s, 2750 s and 4850 s without ionospheric corrections, everything for a roving receiver at more than 100 km far away from the nearest permanent receiver. The real-time horizontal position errors reach up to 3 cm, 5 cm and 12 cm for 50%, 75% and 95% of cases, respectively, by constraining and continuously updating the ambiguities without updating the permanent receiver coordinates, vs. the 6 cm, 12 cm and 32 cm, respectively, in the same conditions but without WARTK ionospheric corrections.
Identifying Coffee Agroforestry System Types Using Multitemporal Sentinel-2 Data and Auxiliary Information
Authors: Escobar-López Agustín , Castillo-Santiago Miguel Ángel , Hernández-Stefanoni José Luis , Mas Jean François , López-Martínez Jorge Omar
Published: August 2022

Coffee is one of the most important agricultural commodities of Mexico. Mapping coffee land cover is still a challenge because it is grown mainly on small areas in agroforestry systems (AFS), which are located in hard-to-access mountainous regions. The objective of this research was to map coffee AFS types in a mountainous region using the changing spectral response patterns over the dry season as well as supplementary data. We employed Sentinel-1, Sentinel-2 and ALOS-Palsar images, a digital elevation model, soil moisture layers, and 150 field plots. First, we defined three coffee AFS types based on their structural and spectral characteristics. Then, we performed a recursive feature elimination analysis to identify the most relevant predictor variables for each land use/cover class in the region. Next, we constructed a predictor variable dataset for each AFS type and one for the remaining land use/cover classes. Afterward, four maps were generated using a random forest (RF) classifier. Finally, we combined the four maps into a unique land-cover map through a maximum likelihood algorithm. Using a validation sample of 932 sites derived from Planet images (4.5 m pixel size), we estimated a 95% map overall accuracy. Two AFS types were classified as having low error; the third, with the highest tree density, had the lowest accuracy. The results obtained show that the infrared and near-infrared bands from the Sentinel-2 scenes are particularly useful for coffee AFS discrimination. However, supplementary data are required to improve the performance of the classifier. Our findings also highlight the importance of the multi-temporal and multi-dataset approach for identifying complex production systems in areas of high topographic heterogeneity.
A Robust Automatic Method to Extract Building Facade Maps from 3D Point Cloud Data
Authors: Yu Bing , Hu Jinlong , Dong Xiujun , Dai Keren , Xiao Dongsheng , Zhang Bo , Wu Tao , Hu Yunliang , Wang Bing
Published: August 2022

Extracting facade maps from 3D point clouds is a fast and economical way to describe a building’s surface structure. Existing methods lack efficiency, robustness, and accuracy, and depend on many additional features such as point cloud reflectivity and color. This paper proposes a robust and automatic method to extract building facade maps. First, an improved 3D Hough transform is proposed by adding shift vote and 3D convolution of the accumulator to improve computational efficiency and reduce peak fuzziness and dependence on the step selection. These modifications make the extraction of potential planes fast and accurate. Second, the coplane and vertical plane constraints are introduced to eliminate pseudoplanes and nonbuilding facades. Then, we propose a strategy to refine the potential facade and to achieve the accurate calibration and division of the adjacent facade boundaries by clustering the refined point clouds of the facade. This process solves the problem where adjoining surfaces are merged into the same surface in the traditional method. Finally, the extracted facade point clouds are converted into feature images. Doors, windows, and building edges are accurately extracted via deep learning and digital image processing techniques, which combine to achieve accurate extraction of building facades. The proposed method was tested on the MLS and TLS point cloud datasets, which were collected from different cities with different building styles. Experimental results confirm that the proposed method decreases computational burden, improves efficiency, and achieves the accurate differentiation of adjacent facade boundaries with higher accuracy compared with the traditional method, verifying the robustness of the method. Additionally, the proposed method uses only point cloud geometry information, effectively reducing data requirements and acquisition costs.
Can Small Industrial Platforms Achieve Large Space Spillover? Identifying the Spatial Spillover Scope of Characteristic Towns Using the Gradient Difference Method
Authors: He Tingting , Song Haipeng , Guo Andong
Published: August 2022

Characteristic towns represent relatively small industrial platforms, characterized by clear industrial positioning, cultural connotations, tourism, and certain community functions. Determining the spatial spillover scope of characteristic towns is of importance for both spatial decision-making and policy optimization. By using the gradient difference method, this paper aims to determine the spatial spillover scope of characteristic towns in 2014 and 2020. The research is based on the nighttime light data of the first three batches of Zhejiang characteristic towns. The results suggest that (1) there is a spatial spillover phenomenon in Zhejiang characteristic towns; namely, the results of 84 characteristic towns are either consistent or partially consistent with the expected results; (2) there is an inverse S-shaped decreasing trend from the boundary of characteristic towns; the trend rapidly decreases with an increase at the boundary distance of characteristic towns; and (3) characteristic towns are formed around the 1 km core spillover area and 2 km secondary spillover area. Provincial characteristic towns have relatively high maturity and account for 43.86% of the total. They are concentrated in the 1 km range. Compared to previous research, this study was able to accurately identify the spatial spillover scope of characteristic towns using the gradient difference method. Specifically, the spatial spillover scope is concentrated primarily in the core spillover area of 1 km. These findings serve as reference for the adjustment and optimization of characteristic town policies as well as of town’s spatial layouts.
One-Shot Multiple Object Tracking in UAV Videos Using Task-Specific Fine-Grained Features
Authors: Wu Han , Nie Jiahao , He Zhiwei , Zhu Ziming , Gao Mingyu
Published: August 2022

Multiple object tracking (MOT) in unmanned aerial vehicle (UAV) videos is a fundamental task and can be applied in many fields. MOT consists of two critical procedures, i.e., object detection and re-identification (ReID). One-shot MOT, which incorporates detection and ReID in a unified network, has gained attention due to its fast inference speed. It significantly reduces the computational overhead by making two subtasks share features. However, most existing one-shot trackers struggle to achieve robust tracking in UAV videos. We observe that the essential difference between detection and ReID leads to an optimization contradiction within one-shot networks. To alleviate this contradiction, we propose a novel feature decoupling network (FDN) to convert shared features into detection-specific and ReID-specific representations. The FDN searches for characteristics and commonalities between the two tasks to synergize detection and ReID. In addition, existing one-shot trackers struggle to locate small targets in UAV videos. Therefore, we design a pyramid transformer encoder (PTE) to enrich the semantic information of the resulting detection-specific representations. By learning scale-aware fine-grained features, the PTE empowers our tracker to locate targets in UAV videos accurately. Extensive experiments on VisDrone2021 and UAVDT benchmarks demonstrate that our tracker achieves state-of-the-art tracking performance.
A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation
Authors: Mao Taoning , Shangguan Wei , Li Qingliang , Li Lu , Zhang Ye , Huang Feini , Li Jianduo , Liu Wei , Zhang Ruqing
Published: August 2022

Remote sensing soil moisture (SM) has been widely used in various earth science studies and applications, but their low resolution limits their usage and downscaling of them is needed. In this study, we proposed a spatial downscaling method for SM based on random forest considering soil moisture memory and mass conservation to improve downscaling performance. The lagged SM was added as a predictor to represent soil moisture memory, in addition to the regular predictors in previous downscaling studies. The Soil Moisture Active Passive (SMAP) SM data of the Pearl River Basin were used to test our downscaling method. The results show that the downscaling model obtained good performance on the test set (R2 = 0.848, ubRMSE = 0.034 m3/m3 and Bias = 0.008 m3/m3). The spatial and temporal performance of the RF downscaling model can be improved by adding lagged SM variables. Downscaled data obtained can retain the information of the original SMAP SM data well and show more spatial details, and mass conservation correction is considered to be useful to eliminate systematic bias of the downscaling model. Downscaled SM achieved acceptable performance in in situ validation, though it was inevitably limited by the performance of the original SMAP data. The proposed downscaling method can serve as a powerful tool for the development of high-resolution SM information.
Evaluation of Gridded Precipitation Data for Hydrologic Modeling in North-Central Texas
Authors: Ray Ram L. , Sishodia Rajendra P. , Tefera Gebrekidan W.
Published: August 2022

Over the past few decades, several high-resolution gridded precipitation products have been developed using multiple data sources and techniques, including measured precipitation, numerical modeling, and remote sensing. Each has its own sets of uncertainties and limitations. Therefore, evaluating these datasets is critical in assessing their applicability in various climatic regions. We used ten precipitation datasets, including measured (in situ), gauge-based, and satellite-based products, to assess their relevance for hydrologic modeling at the Bosque River Basin in North-Central Texas. Evaluated datasets include: (1) in situ station data from the Global Historical Climate Network (GHCN); (2) gauge-based dataset Daymet and the Parameter-elevation Regression on Independent Slope Model (PRISM); (3) satellite-based dataset Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG), Early and Late, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and PERSIANN-CCS (Cloud Classification System); (4) satellite-based gauge-corrected dataset IMERG-Final, PERSIANN-CDR (Climate Data Record), and CHIRPS (Climate Hazards Group Infrared Precipitation with Station data). Daily precipitation data (2000–2019) were used in the Soil and Water Assessment Tool (SWAT) for hydrologic simulations. Each precipitation dataset was used with measured monthly United States Geological Survey (USGS) streamflow data at three locations in the watershed for model calibration and validation. The SUFI-2 (Sequential Uncertainty Fitting) method on the SWAT-CUP (Calibration and Uncertainty Program) was used to quantify and compare the uncertainty in streamflow simulations from all precipitation datasets. The study has also analyzed the uncertainties in SWAT model parameter values under different gridded precipitation datasets. The results showed similar or better model calibration/validation statistics from gauge-based (Daymet and PRISM) and satellite-based gauge-corrected products (CHIRPS) compared with the GHCN data. However, satellite-based precipitation products such as PERSIANN-CCS and PERSIANN-CDR unveil comparatively inferior to capture in situ precipitation and simulate streamflow. The results showed that gauge-based datasets had comparable and even superior performances in some metrics compared with the GHCN data.
Multiple Object Tracking of Drone Videos by a Temporal-Association Network with Separated-Tasks Structure
Authors: Lin Yeneng , Wang Mengmeng , Chen Wenzhou , Gao Wang , Li Lei , Liu Yong
Published: August 2022

The task of multi-object tracking via deep learning methods for UAV videos has become an important research direction. However, with some current multiple object tracking methods, the relationship between object detection and tracking is not well handled, and decisions on how to make good use of temporal information can affect tracking performance as well. To improve the performance of multi-object tracking, this paper proposes an improved multiple object tracking model based on FairMOT. The proposed model contains a structure to separate the detection and ReID heads to decrease the influence between every function head. Additionally, we develop a temporal embedding structure to strengthen the representational ability of the model. By combing the temporal-association structure and separating different function heads, the model’s performance in object detection and tracking tasks is improved, which has been verified on the VisDrone2019 dataset. Compared with the original method, the proposed model improves MOTA by 4.9% and MOTP by 1.2% and has better tracking performance than the models such as SORT and HDHNet on the UAV video dataset.
Remote Estimation of the Particulate Phosphorus Concentrations in Inland Water Bodies: A Case Study in Hongze Lake
Authors: Du Chenggong , Shi Kun , Liu Naisen , Li Yunmei , Lyu Heng , Yan Chen , Pan Jinheng
Published: August 2022

Phosphorus is the most important nutrient associated with lake eutrophication and changes in cyanobacterial blooms, and particulate phosphorus (PP) is the main form of phosphorus found in highly turbid inland waters. Therefore, it is urgent to monitor PP concentrations in inland water bodies. In this study, we take Hongze Lake as the research area and establish a semianalytical model to estimate PP concentrations based on the total particle absorption coefficient (ap); the mean absolute percentage error (MAPE) and root-mean-square error (RMSE) values, which indicate the model accuracy, were 14.90% and 0.009 mg/L, respectively. In addition, the construction process and parameter selection criteria of the remote sensing-based PP concentration estimation model were derived using remote sensing data obtained at different spectral resolutions. Sentinel 3 Ocean and Land Color Instrument (OLCI) and Landsat 9 Operational Land Imager version 2 (OLI-2) data were selected as representatives to verify the accuracy of the model; compared to these two datasets, the MAPE values of the models were 16.32% and 26.84%, respectively, while the RMSE values were 0.010 mg/L and 0.014 mg/L, respectively. Finally, the models were applied to Sentinel 3 OLCI and Landsat 9 OLI-2 images obtained on 16 January 2022. The results show that the spatiotemporal distributions of PP concentrations in Hongze Lake estimated from these two images were relatively consistent, but the OLI data reflected overestimations and underestimations in some areas. These research results provide a new methodology for estimating PP concentrations through remote sensing methods and help to further improve the accuracy of remotely sensed PP concentration estimations in inland water bodies.
DNAS: Decoupling Neural Architecture Search for High-Resolution Remote Sensing Image Semantic Segmentation
Authors: Wang Yu , Li Yansheng , Chen Wei , Li Yunzhou , Dang Bo
Published: August 2022

Deep learning methods, especially deep convolutional neural networks (DCNNs), have been widely used in high-resolution remote sensing image (HRSI) semantic segmentation. In literature, most successful DCNNs are artificially designed through a large number of experiments, which often consume lots of time and depend on rich domain knowledge. Recently, neural architecture search (NAS), as a direction for automatically designing network architectures, has achieved great success in different kinds of computer vision tasks. For HRSI semantic segmentation, NAS faces two major challenges: (1) The task’s high complexity degree, which is caused by the pixel-by-pixel prediction demand in semantic segmentation, leads to a rapid expansion of the search space; (2) HRSI semantic segmentation often needs to exploit long-range dependency (i.e., a large spatial context), which means the NAS technique requires a lot of display memory in the optimization process and can be tough to converge. With the aforementioned considerations in mind, we propose a new decoupling NAS (DNAS) framework to automatically design the network architecture for HRSI semantic segmentation. In DNAS, a hierarchical search space with three levels is recommended: path-level, connection-level, and cell-level. To adapt to this hierarchical search space, we devised a new decoupling search optimization strategy to decrease the memory occupation. More specifically, the search optimization strategy consists of three stages: (1) a light super-net (i.e., the specific search space) in the path-level space is trained to get the optimal path coding; (2) we endowed the optimal path with various cross-layer connections and it is trained to obtain the connection coding; (3) the super-net, which is initialized by path coding and connection coding, is populated with kinds of concrete cell operators and the optimal cell operators are finally determined. It is worth noting that the well-designed search space can cover various network candidates and the optimization process can be done efficiently. Extensive experiments on the publicly open GID and FU datasets showed that our DNAS outperformed the state-of-the-art methods, including artificial networks and NAS methods.
Experimental Measurement of Forward Scattering from Very Rough Sand Ripples in a Water Tank
Authors: Wang Liang , Yu Gaokun , Liang Minshuai , Ren Yun , Peng Linhui
Published: August 2022

High order Bragg scattering from sand ripples is investigated by a tank experiment, where the artificially produced sand ripples have a spatial period of 0.2 m and ripple height of 5 cm. Bragg scattering has been measured at three frequencies 22 kHz, 24.57 kHz, and 27 kHz and three incident grazing angles 20∘, 30∘, 40∘ by a method based on the conventional beamforming using two horizontal receiving arrays. It is illustrated that high order Bragg scatterings can be observed, and the corresponding scattered grazing angles agree with the theoretical prediction. Owing to the ripple height being on the order of wavelength, it is found that the distribution of forward scattering amplitude is different from the distribution for sand ripples of small height, i.e., the diffuseness of scattering amplitude is increased with the ripple height.
Simplified Relations for the Martian Night-Time OH* Suitable for the Interpretation of Observations
Authors: Grygalashvyly Mykhaylo , Shaposhnikov Dmitry S. , Medvedev Alexander S. , Sonnemann Gerd Reinhold , Hartogh Paul
Published: August 2022

Observations of excited hydroxyl (OH*) emissions are broadly used for inferring information about atmospheric dynamics and composition. We present several analytical approximations for characterizing the excited hydroxyl layer in the Martian atmosphere. They include the OH* number density at the maximum and the height of the peak, along with the relations for assessing different impacts on the OH* layer under night-time conditions. These characteristics are determined by the ambient temperature, atomic oxygen concentration, and their vertical gradients. The derived relations can be used for the analysis of airglow measurements and the interpretation of their variations.
Dual-Sideband Constant-Envelope Frequency-Hopping Binary Offset Carrier Multiplexing Modulation for Satellite Navigation
Authors: Ma Jiangang , Yang Yikang , Ye Lvyang , Deng Lingyu , Li Hengnian
Published: August 2022

Frequency-hopping binary offset carrier modulation improves the anti-interference performance and mitigates the autocorrelation function (ACF) ambiguity problem of binary offset carrier modulation. To save payload resources and make high-power amplifiers on satellites operate at the nonlinear saturation region, there is further demand for finding an efficient constant-envelope frequency-hopping binary offset carrier multiplexing technique to combine several signal components. Thus, we propose a dual-sideband constant-envelope multiplexing modulation, named asymmetric constant-envelope frequency-hopping binary offset carrier multiplexing (ACE-FHBOC), which is also a multicarrier constant-envelope multiplexing modulation. ACE-FHBOC provides higher design flexibility in the number of subcarrier frequencies than ACE-BOC while maintaining the same flexibility of signal design as ACE-BOC in the number of signal components and power ratio among components. We first establish the theory and give implementation methods of ACE-FHBOC. Then, we develop a software-defined receiver to simulate and analyze the performance for several specific ACE-FHBOC and ACE-BOC signals. The results show that the recommended ACE-FHBOC signals have lower ACF ambiguity, better anti-narrowband interference, and multipath performance than ACE-BOC under the same conditions. With these advantages, ACE-FHBOC is a promising solution for the signal design of new generation global navigation satellite systems.
Semantic Segmentation of Panoramic Images for Real-Time Parking Slot Detection
Authors: Lai Cong , Yang Qingyu , Guo Yixin , Bai Fujun , Sun Hongbin
Published: August 2022

Autonomous parking is an active field of automatic driving in both industry and academia. Parking slot detection (PSD) based on a panoramic image can effectively improve the perception of a parking space and the surrounding environment, which enhances the convenience and safety of parking. The challenge of PSD implementation is identifying the parking slot in real-time based on images obtained from the around view monitoring (AVM) system, while maintaining high recognition accuracy. This paper proposes a real-time parking slot detection (RPSD) network based on semantic segmentation, which implements real-time parking slot detection on the panoramic surround view (PSV) dataset and avoids the constraint conditions of parking slots. The structural advantages of the proposed network achieve real-time semantic segmentation while effectively improving the detection accuracy of the PSV dataset. The cascade structure reduces the operating parameters of the whole network, ensuring real-time performance, and the fusion of coarse and detailed features extracted from the upper and lower layers improves segmentation accuracy. The experimental results show that the final mIoU of this work is 67.97% and the speed is up to 32.69 fps, which achieves state-of-the-art performance with the PSV dataset.
Water Occurrence in the Two Largest Lakes in China Based on Long-Term Landsat Images: Spatiotemporal Changes, Ecological Impacts, and Influencing Factors
Authors: Deng Yue , Jiang Weiguo , Ye Xuchun , Zhang Lin , Jia Kai
Published: August 2022

Poyang Lake and Dongting Lake are the two largest freshwater lakes in China. They play a critical ecological role in regional sustainable development, which is closely related to water occurrence (WO). This study aimed to characterize the spatiotemporal changes, ecological impacts, and influencing factors of WO in the two lakes. First, this study utilized the Google Earth Engine (GEE) platform and all available Landsat images to retrieve the time series of WO in Poyang Lake and Dongting Lake on a two-year scale from 1989 to 2020. Then, the study explored the landscape variation intensity, landscape structure, and their ecological impacts on net primary production (NPP) and total nitrogen (TN) based on the landscape transfer rate (LTR), landscape indices, and geostatistical connectivity analysis. Finally, the study investigated the natural and human factors that influence the changes in WO. The major conclusions include the following: (1) the mean WO showed a significantly decreasing trend in the two lakes from 1989 to 2020. According to the LTR, the landscape variation in Dongting Lake was more intense before 2002, while after 2002, the landscape variation in Poyang Lake was more intense. (2) The landscape structure of WO gradually fragmented and diversified, along with decreasing hydrological connectivity in the two lakes. (3) The increase in NPP in Poyang Lake and the increase in TN in Dongting Lake were closely correlated with the changes in WO. (4) The upstream runoff showed a significantly positive correlation with the mean WO in Poyang Lake and the annual precipitation showed a significantly positive correlation with the mean WO in Dongting Lake; the influences of natural factors on WO changes became weaker. This study reinforces the understanding of long-term changes in the water body in Poyang Lake and Dongting Lake.
Accurate Spatial Positioning of Target Based on the Fusion of Uncalibrated Image and GNSS
Authors: Liang Binbin , Han Songchen , Li Wei , Fu Daoyong , He Ruliang , Huang Guoxin
Published: August 2022

The accurate spatial positioning of the target in a fixed camera image is a critical sensing technique. Conventional visual spatial positioning methods rely on tedious camera calibration and face great challenges in selecting the representative feature points to compute the position of the target, especially when existing occlusion or in remote scenes. In order to avoid these deficiencies, this paper proposes a deep learning approach for accurate visual spatial positioning of the targets with the assistance of Global Navigation Satellite System (GNSS). It contains two stages: the first stage trains a hybrid supervised and unsupervised auto-encoder regression network offline to gain capability of regressing geolocation (longitude and latitude) directly from the fusion of image and GNSS, and learns an error scale factor to evaluate the regression error. The second stage firstly predicts regressed accurate geolocation online from the observed image and GNSS measurement, and then filters the predictive geolocation and the measured GNSS to output the optimal geolocation. The experimental results showed that the proposed approach increased the average positioning accuracy by 56.83%, 37.25%, 41.62% in a simulated scenario and 31.25%, 7.43%, 38.28% in a real-world scenario, compared with GNSS, the Interacting Multiple Model−Unscented Kalman Filters (IMM-UKF) and the supervised deep learning approach, respectively. Other improvements were also achieved in positioning stability, robustness, generalization, and performance in GNSS denied environments.