bluuebunny/crossref_metadata_2025 huggingface dataset:
Can Electrophysiological Parameters Substitute for Growth, and Photosynthetic Parameters to Characterize the Response of Mulberry and Paper Mulberry to Drought?
Authors: Yu Rui , Wu Yanyou , Xing Deke
Published: August 2021

Drought is a key factor restricting plant survival, growth and development. The physiological parameters of plants are commonly used to determine the water status, in order to irrigate appropriately and save water. In this study, mulberry (Morus alba L.) and paper mulberry (Broussonetia papyrifera (L.) Vent.) seedlings were used as experimental materials, and four soil moisture treatments were set up for both plant species: 70–75% (CK: the control group, referred to as T0), 55–60% (T1: mild drought), 40–45% (T2: moderate drought), and 25–30% (T3: severe drought). The growth parameter of the plants was measured every two days from the onset of the treatment, the photosynthetic and electrophysiological parameters of the plants were measured every other week for a total of five times. The physiological responses and electrophysiological traits of leaves under different treatment levels were analyzed. The results showed that the photosynthetic and electrophysiological parameters could characterize the response of mulberry growth and development to soil water, and the growth and electrophysiological parameters could characterize the response of paper mulberry growth and development to soil water. Mild drought had no significant effects on the growth and development of mulberry and paper mulberry.
New Principles of Polymer Composite Preparation. MQ Copolymers as an Active Molecular Filler for Polydimethylsiloxane Rubbers
Authors: Meshkov Ivan , Kalinina Aleksandra , Gorodov Vadim , Bakirov Artem , Krasheninnikov Sergey , Chvalun Sergei , Muzafarov Aziz
Published: August 2021

Colorless transparent vulcanizates of silicone elastomers were prepared by mixing the components in a common solvent followed by solvent removal. We studied the correlation between the mechanical behavior of polydimethylsiloxane (PDMS)-rubber compositions prepared using MQ (mono-(M) and tetra-(Q) functional siloxane) copolymers with different ratios of M and Q parts as a molecular filler. The composition and molecular structure of the original rubber, MQ copolymers, and carboxyl-containing PDMS oligomers were also investigated. The simplicity of the preparation of the compositions, high strength and elongation at break, and their variability within a wide range allows us to consider silicone elastomers as a promising alternative to silicone materials prepared by traditional methods.
Selective Production of Bio-Based Linear Alpha-Olefin from Wasted Fatty Alcohol on Al2O3 for Bio-Based Chemicals
Authors: Lee Hye-Jin , Choi Il-Ho , Kim Seung-Wook , Hwang Kyung-Ran
Published: August 2021

The catalytic dehydration of a bio-based fatty alcohol was performed using Al2O3 prepared by solvothermal synthesis for selective production of long-chain linear-alpha-olefins (LAO). The effect of the synthesis temperature of alumina precursors on the dehydration of 1-octadecanol (C18H38O) was examined based on the textural properties and Lewis acid–base properties of the catalysts. Amorphous alumina synthesized at 325 °C showed the highest surface area (233.07 m2/g) and total pore volume (1.237 cm3/g) among the catalysts and the best dehydration results: 93% conversion, 62% selectivity of 1-octadecene (C18H36), and 89% LAO purity. This was attributed to the increased Al/O ratio and atomic concentration of surface O in alumina, which were important factors in the catalytic dehydration of 1-octadecanol through the synergistic catalysis of acid–base pairs. The produced bio-based LAO can be key intermediates for synthesis of oxo alcohols and poly-alpha-olefins, as alternatives to petroleum-based LAO to achieve carbon neutrality in chemical industry.
Hydrophobically Grafted Pullulan Nanocarriers for Percutaneous Delivery: Preparation and Preliminary In Vitro Characterisation
Authors: Bostanudin Mohammad F. , Barbu Eugen , Liew Kai Bin
Published: August 2021

Polymeric colloidal nanocarriers formulated from hydrophobically grafted carbohydrates have been the subject of intensive research due to their potential to increase the percutaneous penetration of hydrophilic actives. To this goal, a series of hydrophobically grafted pullulan (BMO-PUL) derivatives with varying degree of grafting (5–64%) was prepared through functionalisation with 2-(butoxymethyl)oxirane. The results demonstrated that monodispersed BMO-PUL nanocarriers (size range 125–185 nm) could be easily prepared via nanoprecipitation; they exhibit close-to-spherical morphology and adequate stability at physiologically relevant pH. The critical micellar concentration of BMO-PUL was found to be inversely proportional to their molecular weight (Mw) and degree of grafting (DG), with values of 60 mg/L and 40 mg/L for DG of 12.6% and 33.8%, respectively. The polymeric nanocarriers were loaded with the low Mw hydrophilic active α-arbutin (16% loading), and the release of this active was studied at varying pH values (5 and 7), with a slightly faster release observed in acidic conditions; the release profiles can be best described by a first-order kinetic model. In vitro investigations of BMO-PUL nanocarriers (concentration range 0.1–4 mg/mL) using immortalised skin human keratinocytes cells (HaCaT) evidenced their lack of toxicity, with more than 85% cell viability after 24 h. A four-fold enhance in arbutin permeation through HaCaT monolayers was recorded when the active was encapsulated within the BMO-PUL nanocarriers. Altogether, the results obtained from the in vitro studies highlighted the potential of BMO-PUL nanocarriers for percutaneous delivery applications, which would warrant further investigation in vivo.
Nanocelluloses Reinforced Bio-Waterborne Polyurethane
Authors: Hormaiztegui M. E. Victoria , Marin Diana , Gañán Piedad , Stefani Pablo Marcelo , Mucci Verónica , Aranguren Mirta I.
Published: August 2021

The aim of this work was to evaluate the influence of two kinds of bio- nano-reinforcements, cellulose nanocrystals (CNCs) and bacterial cellulose (BC), on the properties of castor oil-based waterborne polyurethane (WBPU) films. CNCs were obtained by the acidolysis of microcrystalline cellulose, while BC was produced from Komagataeibacter medellinensis. A WBPU/BC composite was prepared by the impregnation of a wet BC membrane and further drying, while the WBPU/CNC composite was obtained by casting. The nanoreinforcement was adequately dispersed in the polymer using any of the preparation methods, obtaining optically transparent compounds. Thermal gravimetric analysis, Fourier-transform infrared spectroscopy, field emission scanning electron microscopy, dynamical mechanical analysis, differential scanning calorimetry, contact angle, and water absorption tests were carried out to analyze the chemical, physical, and thermal properties, as well as the morphology of nanocelluloses and composites. The incorporation of nanoreinforcements into the formulation increased the storage modulus above the glass transition temperature of the polymer. The thermal stability of the BC-reinforced composites was slightly higher than that of the CNC composites. In addition, BC allowed maintaining the structural integrity of the composites films, when they were immersed in water. The results were related to the relatively high thermal stability and the particular three-dimensional interconnected reticular morphology of BC.
Flame Retardancy and Excellent Electrical Insulation Performance of RTV Silicone Rubber
Authors: Nazir Muhammad Tariq , Khalid Arslan , Kabir Imrana , Wang Cheng , Baena Juan-Carlos , Akram Shakeel , Bhutta Muhammad Shoaib , Yasin Ghulam , Phung Bao Toan , Yeoh Guan Heng
Published: August 2021

Room temperature vulcanized (RTV) silicone rubber filled with aluminum trihydrate (ATH) is substantially engaged in electrical outdoor insulation applications. The pristine silicone rubber is highly combustible. ATH filled silicone rubber offers excellent electrical insulation but lacks in providing adequate flame retardancy. This short communication reports the novel results on improved flame retardancy of pristine and ATH filled silicone rubber whilst retaining the electrical insulation properties to a great extent. Results suggest that the presence of only one percent of graphene nanoplatelets with ATH sharply reduces the heat release rate and rate of smoke release. A minor reduction in dielectric breakdown strength and volume resistivity is noticed. Furthermore, permittivity and dielectric loss at power frequency suggest that a marginal 1% concentration of nanoplatelet with ATH is an excellent approach to fabricate flame retardant silicone rubber with an acceptable electrical insulation level.
Application of β-Tricalcium Phosphate in Adhesive Dentin Bonding
Authors: AlRefeai Mohammad H. , AlHamdan Eman M. , Al-Saleh Samar , Alqahtani Abdulaziz S. , Al-Rifaiy Mohammad Q. , Alshiddi Ibraheem F. , Farooq Imran , Vohra Fahim , Abduljabbar Tariq
Published: August 2021

The study aimed at synthesizing β-tricalcium phosphate (β-TCP) nanoparticles and comparing the mechanical properties and dentin interaction of two adhesives: experimental adhesive (EA) and EA with 5 wt.% β-TCP nanoparticles (β-TCP-5%). These filler nanoparticles were synthesized and then characterized with scanning electron microscopy (SEM) and micro-Raman spectroscopy. The β-TCP nanoparticles were incorporated in the adhesives to form two groups: gp-1: EA (control) and gp-2: β-TCP-5%. These adhesives were characterized by SEM, energy-dispersive X-ray (EDX) spectroscopy and were also assessed for their micro-tensile bond strength (μTBS) with (TC) and without thermocycling (NTC). Fourier Transform Infrared (FTIR) spectroscopy was performed to evaluate the degree of conversion (DC) of two adhesives. The β-TCP filler was seen as irregularly shaped agglomerates on SEM. The micro-Raman spectra revealed characteristic peaks associated with β-TCP nanoparticles. Both adhesives presented suitable dentin interaction, which was demonstrated by the formation of resin tags of variable depths. The EDX analysis verified the existence of calcium (Ca) and phosphate (P) for the β-TCP-5% group. The greatest μTBS values were shown by β-TCP-5% group samples when they were non-thermocycled (NTC) (β-TCP-5%-NTC: 34.11 ± 3.46) followed by the thermocycled (TC) samples of the same group (β-TCP-5%-TC: 30.38 ± 3.66), compared with the EA group. Although the DC presented by β-TCP-5% group was comparable to the EA group, it was still lower. The addition of β-TCP nanoparticles in the adhesive improved its μTBS and resulted in a suitable dentin interaction, seen in the form of hybrid layer and resin tag formation. Nonetheless, a decreased DC was observed for the β-TCP-5% adhesive. Future studies probing the effect of different filler concentrations on various properties of the adhesive are warranted.
Insights on the Atmospheric-Pressure Plasma-Induced Free-Radical Polymerization of Allyl Ether Cyclic Carbonate Liquid Layers
Authors: Niemczyk Edyta M. , Gomez-Lopez Alvaro , Haler Jean R. N. , Frache Gilles , Sardon Haritz , Quintana Robert
Published: August 2021

Plasma-induced free-radical polymerizations rely on the formation of radical species to initiate polymerization, leading to some extent of monomer fragmentation. In this work, the plasma-induced polymerization of an allyl ether-substituted six-membered cyclic carbonate (A6CC) is demonstrated and emphasizes the retention of the cyclic carbonate moieties. Taking advantage of the low polymerization tendency of allyl monomers, the characterization of the oligomeric species is studied to obtain insights into the effect of plasma exposure on inducing free-radical polymerization. In less than 5 min of plasma exposure, a monomer conversion close to 90% is obtained. The molecular analysis of the oligomers by gel permeation chromatography coupled with high-resolution mass spectrometry (GPC-HRMS) further confirms the high preservation of the cyclic structure and, based on the detected end groups, points to hydrogen abstraction as the main contributor to the initiation and termination of polymer chain growth. These results demonstrate that the elaboration of surfaces functionalized with cyclic carbonates could be readily elaborated by atmospheric-pressure plasmas, for instance, by copolymerization.
Synthesis of a Compound Phosphorus-Nitrogen Intumescent Flame Retardant for Applications to Raw Lacquer
Authors: Shiu Bing-Chiuan , Wu Kunlin , Lou Ching-Wen , Lin Qi , Lin Jia-Horng
Published: August 2021

Raw lacquer (RL) is a natural polymer compound with highly promising applications; however, its inflammable attribute restricts the industrial applications. In this study, melamine is used to formulate tri (1-melamine-2-propanol) phosphate (FR-1), after which it is synthesized with ammonium phosphate (FR-2) and diatomite to form a compound phosphorus-nitrogen intumescent flame retardant (IFR). Next, IFR is used as the filling agent that then cross-links with RL, and as such RL/IFR membranes are formed after the curing. The limiting oxygen index (LOI) measurement, the vertical combustion test (UL-94), the microshape calorimetric analysis (CCT), and the thermal gravimetric analysis (TGA) are conducted to examine the combustion resistance and thermal stability of the membranes. Fourier transform infrared spectroscopy (FT-IR) and electron scanning microscope (SEM) are performed to separately characterize the structure and compatibility; the mechanical properties of the membranes are also evaluated. The vertical combustion test results confirm that with 30 wt% of IFR, RL/IFR membranes acquire 12.3% higher LOI and a vertically combustion of V-0 level. The TGA indicates that RL/IFR membranes demonstrate a greater adhesion level, a higher rigidity, and better luster than pure RL membranes.
Enhancement of Gel Strength of Itaconic Acid-Based Superabsorbent Polymer Composites Using Oxidized Starch
Authors: Kim Haechan , Kim Jungsoo , Kim Donghyun
Published: August 2021

Herein, core-superabsorbent polymer (CSAP) composites are prepared from oxidized starch (OS) via aqueous solution copolymerization using ammonium persulfate as the initiator, and 1,6-hexanediol diacrylate as the inner-crosslinker. The surface-crosslinking process is performed using various surface-crosslinkers, including bisphenol A diglycidyl ether (BADGE), poly(ethylene glycol) diglycidyl ether (PEGDGE), ethylene glycol diglycidyl ether (EGDGE), and diglycidyl ether (DGE). The structures of the CSAP composites and their surface-crosslinked SAPs (SSAPs) are characterized using Fourier transform infrared (FT-IR) spectroscopy, their absorption properties are measured via centrifuge retention capacity (CRC), absorbency under load (AUL), permeability, and re-swellability tests, and their gel strengths according to surface-crosslinker type and EGDGE content are examined via rheological analysis. The results indicate that an EGDGE content of 0.75 mol provides the optimum surface-crosslinking and SSAP performance, with a CRC of 34.8 g/g, an AUL of 27.2 g/g, and a permeability of 43 s. The surface-crosslinking of the CSAP composites using OS is shown to improve the gel strength, thus enabling the SAP to be used in disposable diapers.
Development of Highly Crystalline Polylactic Acid with β-Crystalline Phase from the Induced Alignment of Electrospun Fibers
Authors: Echeverría Coro , Limón Irene , Muñoz-Bonilla Alexandra , Fernández-García Marta , López Daniel
Published: August 2021

Polylactic acid (PLA) is one of the known synthetic polymers with potential piezoelectric activity but this property is directly related to both the crystalline structure and crystalline degree. Depending on the process conditions, PLA can crystallize in three different forms: α-, β-, and γ- form, with β-crystalline phase being the piezoelectric one. To obtain this crystalline structure, transformation of α to β is required. To do so, the strategies followed so far consisted in annealing or/and stretching of previously obtained PLA in the form of films or fibers, that is, additional post-processing steps. In this work, we are able to obtain PLA fibers with high macromolecular alignment, as demonstrated by SEM, and in the β polymorph, as detected by X-ray diffraction (XRD) without the requirement of post-processing. For that, PLA fibers were prepared by using an electrospinning coupled to a drum collector. This set up and the optimization of the parameters (voltage flow-rate, and drum collector speed) induced molecular stretching giving rise to uniaxially oriented and highly aligned fibers.
Study on the Creep-Sliding Mechanism of the Giant Xiongba Ancient Landslide Based on the SBAS-InSAR Method, Tibetan Plateau, China
Authors: Guo Changbao , Yan Yiqiu , Zhang Yongshuang , Zhang Xujiao , Zheng Yueze , Li Xue , Yang Zhihua , Wu Ruian
Published: August 2021

The geohazards associated with strongly deformed and reactivated large-scale ancient landslide are analyzed through a study of the Xiongba ancient landslide. The SBAS-InSAR method, combined with remote sensing interpretation, was used to obtain the Xiongba ancient landslide surface deformation characteristics, on the western bank of the Jinsha River, during the period from October 2017 to June 2020. Two large strong deformation zones were discovered in this study, H1 and H2, which were located at the front edge of the Xiongba landslide. The maximum cumulative deformation in the H1 deformation zone was approximately 204 mm, and the deformation in the H2 deformation zone was approximately 302 mm. Influenced by the Jinsha River erosion, the Baige landslide-dammed lake-dam breakage-debris (LDLDB) flow/flood hazard chains, which occurred 75 km upstream reaches in October and November 2018, and the erosion of the foot of the Xiongba ancient landslide foot resulted in notably enhanced deformation. The creep rate in the H1 deformation zone was 14~16 times that before the Baige landslide hazard chains occurred, and the hazard chains caused sliding in the H2 zone. The Xiongba ancient landslide is undergoing retrogressive reactivation. The Xiongba ancient landslide is currently experiencing continuously creep-sliding, and the deformation rate in some areas is accelerating, which may induce a large-scale reactivation of the Xiongba ancient landslide and an LDLDB hazard chain.
3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation
Authors: Wei Shunjun , Zhou Zichen , Wang Mou , Wei Jinshan , Liu Shan , Shi Jun , Zhang Xiaoling , Fan Fan
Published: August 2021

Millimeter-wave (MMW) 3-D imaging technology is becoming a research hotspot in the field of safety inspection, intelligent driving, etc., due to its all-day, all-weather, high-resolution and non-destruction feature. Unfortunately, due to the lack of a complete 3-D MMW radar dataset, many urgent theories and algorithms (e.g., imaging, detection, classification, clustering, filtering, and others) cannot be fully verified. To solve this problem, this paper develops an MMW 3-D imaging system and releases a high-resolution 3-D MMW radar dataset for imaging and evaluation, named as 3DRIED. The dataset contains two different types of data patterns, which are the raw echo data and the imaging results, respectively, wherein 81 high-quality raw echo data are presented mainly for near-field safety inspection. These targets cover dangerous metal objects such as knives and guns. Free environments and concealed environments are considered in experiments. Visualization results are presented with corresponding 2-D and 3-D images; the pixels of the 3-D images are 512×512×6. In particular, the presented 3DRIED is generated by the W-band MMW radar with a center frequency of 79GHz, and the theoretical 3-D resolution reaches 2.8 mm × 2.8 mm × 3.75 cm. Notably, 3DRIED has 5 advantages: (1) 3-D raw data and imaging results; (2) high-resolution; (3) different targets; (4) applicability for evaluation and analysis of different post processing. Moreover, the numerical evaluation of high-resolution images with different types of 3-D imaging algorithms, such as range migration algorithm (RMA), compressed sensing algorithm (CSA) and deep neural networks, can be used as baselines. Experimental results reveal that the dataset can be utilized to verify and evaluate the aforementioned algorithms, demonstrating the benefits of the proposed dataset.
Generalized Dechirp-Keystone Transform for Radar High-Speed Maneuvering Target Detection and Localization
Authors: Zheng Jibin , Zhu Kangle , Niu Zhiyong , Liu Hongwei , Liu Qing Huo
Published: August 2021

The multivariate range function of the high-speed maneuvering target induces modulations on both the envelop and phase, i.e., the range cell migration (RCM) and Doppler frequency migration (DFM) which degrade the long-time coherent integration used for detection and localization. To solve this problem, many long-time coherent integration methods have been proposed. Based on mechanisms of typical methods, this paper names two signal processing modes, i.e., processing unification (PU) mode and processing separation (PS) mode, and presents their general forms. Thereafter, based on the principle of the PS mode, a novel long-time coherent integration method, known as the generalized dechirp-keystone transform (GDKT), is proposed for radar high-speed maneuvering target detection and localization. The computational cost, energy integration, peak-to-sidelobe level (PSL), resolution, and anti-noise performance of the GDKT are analyzed and compared with those of the maximum likelihood estimation (MLE) method and keystone transform-dechirp (KTD) method. With mathematical analyses and numerical simulations, we validate two main superiorities of the GDKT, including (1) the statistically optimal anti-noise performance, and (2) the low computational cost. The real radar data is also used to validate the GDKT. It is worthwhile noting that, based on closed analytical formulae of the MLE method, KTD method, and GDKT, several doubts in radar high-speed maneuvering target detection and localization are mathematically interpreted, such as the blind speed sidelobe (BSSL) and the relationship between the PU and PS modes.
Using Field Spectroradiometer to Estimate the Leaf N/P Ratio of Mixed Forest in a Karst Area of Southern China: A Combined Model to Overcome Overfitting
Authors: He Wen , Li Yanqiong , Wang Jinye , Yao Yuefeng , Yu Ling , Gu Daxing , Ni Longkang
Published: August 2021

The ratio between nitrogen and phosphorus (N/P) in plant leaves has been widely used to assess the availability of nutrients. However, it is challenging to rapidly and accurately estimate the leaf N/P ratio, especially for mixed forest. In this study, we collected 301 samples from nine typical karst areas in Guangxi Province during the growing season of 2018 to 2020. We then utilized five models (partial least squares regression (PLSR), backpropagation neural network (BPNN), general regression neural network (GRNN), PLSR+BPNN, and PLSR+GRNN) to estimate the leaf N/P ratio of plants based on these samples. We also applied the fractional differentiation to extract additional information from the original spectra of each sample. The results showed that the average leaf N/P ratio of plants was 17.97. Plant growth was primarily limited by phosphorus in these karst areas. The sensitive spectra to estimate leaf N/P ratio had wavelengths ranging from 400–730 nm. The prediction capabilities of these five models can be ranked in descending order as PLSR+GRNN, PLSR+BPNN, PLSR, GRNN, and BPNN when considering both accuracy and robustness. The PLSR+GRNN model yielded high R2 and performance to deviation (RPD), and low root mean squared error (RMSE) with values of 0.91, 3.15, and 1.98, respectively, for the training test and 0.81, 2.25, and 2.46, respectively, for validation test. Compared with the PLSR model, both PLSR+BPNN and PLSR+GRNN models had higher accuracy and were more stable. Moreover, both PLSR+BPNN and PLSR+GRNN models overcame the issue of overfitting, which occurs when a single model is used to predict leaf N/P ratio. Therefore, both PLSR+BPNN and PLSR+GRNN models can be used to predict the leaf N/P ratio of plants in karst areas. Fractional differentiation is a promising spectral preprocessing technique that can improve the accuracy of models. We conclude that the leaf N/P ratio of mixed forest can be effectively estimated using combined models based on field spectroradiometer data in karst areas.
Analysis of Seismic Deformation from Global Three-Decade GNSS Displacements: Implications for a Three-Dimensional Earth GNSS Velocity Field
Authors: Ren Yingying , Lian Lizhen , Wang Jiexian
Published: August 2021

With the rapid development of Global Navigation Satellite System (GNSS) technology, the long-term accumulated GNSS observations of global reference stations have provided valuable data for geodesy and geodynamics studies since the 1990s. Acquiring the precise velocity of GNSS stations is very important for the study of global plate movement, crustal deformation, etc. However, the seismic activities nearby some GNSS observation stations may seriously change the station’s motion trajectory. Therefore, our research was motivated to propose a method allowing for station seismic deformation, and apply it to construct an updated global GNSS velocity field. The main contributions of this work included the following. Firstly, we improved the GNSS data processing procedures and seismic data selection strategies to obtain GNSS coordinate time series with mm-level precision (3–5 and 6–8 mm in the horizontal and vertical, respectively) and information of each site impacted by seismic events, which provides necessary input data for further analysis. Secondly, an Integrated Time Series Method (ITSM) concerning the effect of seismic deformation was proposed to model the station’s nonlinear motion accurately. Distinguished with existing studies, all parameters including seismic relaxation time can be simultaneously estimated by ITSM, which improves the accuracy and reliability of GNSS station velocity significantly. Thirdly, to optimize the ITSM-based model, the influences of seismic relaxation time (a. 0.1 × true, b. 10 × true, c. true), parameterization mode (a. Offset + Velocity, b. Offset + Velocity + PSD, c. Offset + Velocity + PSD + Period), and the Post-Seismic Deformation (PSD) model (a. None, b. Exp, c. Log, d. Exp + Log) on results of GNSS time series analyzing were discussed. The results showed that the fitting accuracy of GNSS displacements was better than 5 mm and 10 mm in the horizontal and vertical, respectively. Finally, the global GNSS station velocity field (referred to as GGV2020 hereafter) was refined by ITSM using global GNSS observations and seismic data during 1990–2020. This not only helps interpret plate tectonic motion, establish and maintain a Dynamic Terrestrial Reference Frame (DTRF) but also contributes to better investigating geodynamic processes. GGV2020 results showed that the accuracy of global velocity was better than 1 mm/a, and the averages of Root Mean Square Error (RMSE) were 0.19 mm/a, 0.19 mm/a, and 0.33 mm/a in the north, east, and up direction, respectively. Besides, the RMSE obeys normal distribution. Compared with ITRF2014, there was a difference of about 1–2 mm/a between them due to differences in terms of observation span, processing model, and geodetic technology. Moreover, GGV2020 is expected to enrich and update the existing velocity field products to describe the characteristics of regional crustal movement in more detail, especially in Antarctica.
Snow Lapse Rate Changes in the Atlas Mountain in Morocco Based on MODIS Time Series during the Period 2000–2016
Authors: Marchane Ahmed , Boudhar Abdelghani , Baba Mohammed Wassim , Hanich Lahoucine , Chehbouni Abdelghani
Published: August 2021

The spatio-temporal distribution of snow cover metrics in a mountainous area is mainly related to the climatic conditions as well as to the prevailing morphological conditions. The present study aimed to investigate the altitudinal sensitivity of snow cover metrics using the MODIS Terra snow cover product (MOD10A1 v5). Annual snow metrics, including start of snow season (SOSS), end of snow season (EOSS), and snow cover duration (SCD) were extracted from snow-covered area (SCA) maps, which had been pre-processed using a cloud removal algorithm; the maps were of the Atlas Mountains, taken from the period of 2001–2016. In addition, a linear regression was applied to derive an annual altitudinal gradient for each snow metric in relation to various spatial scales in order to analyze the interdependency between snow and topography, and especially to assess the potential temporal trend of the snow gradient. Results indicated that elevation was the principal regulator of snow presence where snow was mostly accumulated above 2500 m. The annual altitudinal gradients for EOSS and SCD showed a marked negative trend beginning in 2007. However, the SOSS altitudinal gradient was marked by a positive trend. The mean SCD gradient for the entire Atlas Mountains decreased from 6 days/100 m to 3 days/100 m. This is a new and important finding since it may indicate the impact of climate change on the dynamics of snow metrics and provides guidance for water managers to better manage the snowmelt water with different terrain features.
Wave Peel Tracking: A New Approach for Assessing Surf Amenity and Analysis of Breaking Waves
Authors: Thompson Michael , Zelich Ivan , Watterson Evan , Baldock Tom E.
Published: August 2021

The creation and protection of surfing breaks along populated coastlines have become a consideration for many councils and governments as surfing breaks are a major driver of tourism. To assess the surf amenity of surfing breaks, a quantitative and objective assessment method is required. A new wave peel tracking (WPT) method has been developed using a shore-based camera to assess surf amenity by measuring and quantifying potential surfing ride rate, length, duration, speed and direction on a wave-by-wave basis. The wave peel (or “curl” below the wave peak) is the optimal surfing region on a wave, and each wave peel track represents a surfable ride. Wave peel regions are identified, classified and tracked using traditional and machine learning-based computer vision techniques. The methodology is validated by comparing the rectified wave peel tracks with GPS-measured tracks from surfers in the wave peel regions. The WPT methodology is evaluated with data from a reef and adjacent natural beach at the Gold Coast, Australia. The reef produced longer ride lengths than the nearshore region and showed a consistent breaking location along the reef crest. Spatial maps of the wave peel tracks show the influence of tides on the wave breaking patterns and intensity. The WPT algorithm provides a robust, automated method for quantifying surf amenity to provide baseline data for surf break conservation. The methodology has potential uses to verify numerical modelling of surf breaks and to assess the impact of coastal development on surf breaks.
Modal Parameters Identification of Bridge Structures from GNSS Data Using the Improved Empirical Wavelet Transform
Authors: Fang Zhen , Yu Jiayong , Meng Xiaolin
Published: August 2021

It is difficult to accurately identify the dynamic deformation of bridges from Global Navigation Satellite System (GNSS) due to the influence of the multipath effect and random errors, etc. To solve this problem, an improved empirical wavelet transform (EWT)-based procedure was proposed to denoise GNSS data and identify the modal parameters of bridge structures. Firstly, the Yule–Walker algorithm-based auto-power spectrum and Fourier spectrum were jointly adopted to segment the frequency bands of structural dynamic response data. Secondly, the improved EWT algorithm was used to decompose and reconstruct the dynamic response data according to a correlation coefficient-based criterion. Finally, Natural Excitation Technique (NExT) and Hilbert Transform (HT) were applied to identify the modal parameters of structures from the decomposed efficient components. Two groups of simulation data were used to validate the feasibility and reliability of the proposed method, which consisted of the vibration responses of a four-storey steel frame model, and the acceleration response data of a suspension bridge. Moreover, field experiments were carried out on the Wilford suspension bridge in Nottingham, UK, with GNSS and an accelerometer. The fundamental frequency (1.6707 Hz), the damping ratio (0.82%), as well as the maximum dynamic displacements (10.10 mm) of the Wilford suspension bridge were detected by using this proposed method from the GNSS measurements, which were consistent with the accelerometer results. In conclusion, the analysis revealed that the improved EWT-based method was capable of accurately identifying the low-order, closely spaced modal parameters of bridge structures under operational conditions.
Spectral and Growth Characteristics of Willows and Maize in Soil Contaminated with a Layer of Crude or Refined Oil
Authors: Serrano-Calvo Raquel , Cutler Mark E. J. , Bengough Anthony Glyn
Published: August 2021

Remote sensing holds great potential for detecting stress in vegetation caused by hydrocarbons, but we need to better understand the effects of hydrocarbons on plant growth and specific spectral expression. Willow (Salix viminalis var. Tora) cuttings and maize (Zea mays var. Lapriora) seedlings were grown in pots of loam soil containing a hydrocarbon-contaminated layer at the base of the pot (crude or refined oil) at concentrations of 0.5, 5, or 50 g·kg−1. Chlorophyll concentration, biomass, and growth of plants were determined through destructive and nondestructive sampling, whilst reflectance measurements were made using portable hyperspectral spectrometers. All biophysical (chlorophyll concentration and growth) variables decreased in the presence of high concentrations of hydrocarbons, but at lower concentrations an increase in growth and chlorophyll were often observed with respect to nonpolluted plants, suggesting a biphasic response to hydrocarbon presence. Absorption features were identified that related strongly to pigment concentration and biomass. Variations in absorption feature characteristics (band depth, band area, and band width) were dependent upon the hydrocarbon concentration and type, and showed the same biphasic pattern noted in the biophysical measurements. This study demonstrates that the response of plants to hydrocarbon pollution varies according to hydrocarbon concentration and that remote sensing has the potential to both detect and monitor the variable impacts of pollution in the landscape.
Crop Classification of Satellite Imagery Using Synthetic Multitemporal and Multispectral Images in Convolutional Neural Networks
Authors: Siesto Guillermo , Fernández-Sellers Marcos , Lozano-Tello Adolfo
Published: August 2021

The demand for new tools for mass remote sensing of crops, combined with the open and free availability of satellite imagery, has prompted the development of new methods for crop classification. Because this classification is frequently required to be completed within a specific time frame, performance is also essential. In this work, we propose a new method that creates synthetic images by extracting satellite data at the pixel level, processing all available bands, as well as their data distributed over time considering images from multiple dates. With this approach, data from images of Sentinel-2 are used by a deep convolutional network system, which will extract the necessary information to discern between different types of crops over a year after being trained with data from previous years. Following the proposed methodology, it is possible to classify crops and distinguish between several crop classes while also being computationally low-cost. A software system that implements this method has been used in an area of Extremadura (Spain) as a complementary monitoring tool for the subsidies supported by the Common Agricultural Policy of the European Union.
Using Sentinel-2 for Simplifying Soil Sampling and Mapping: Two Case Studies in Umbria, Italy
Authors: Santaga Francesco Saverio , Agnelli Alberto , Leccese Angelo , Vizzari Marco
Published: August 2021

Soil-sample collection and strategy are costly and time-consuming endeavors, mainly when the goal is in-field variation mapping that usually requires dense sampling. This study developed and tested a streamlined soil mapping methodology, applicable at the field scale, based on an unsupervised classification of Sentinel-2 (S2) data supporting the definition of reduced soil-sampling schemes. The study occurred in two agricultural fields of 20 hectares each near Deruta, Umbria, Italy. S2 images were acquired for the two bare fields. After a band selection based on bibliography, PCA (Principal Component Analysis) and cluster analysis were used to identify points of two reduced-sample schemes. The data obtained by these samplings were used in linear regressions with principal components of the selected S2 bands to produce maps for clay and organic matter (OM). Resultant maps were assessed by analyzing residuals with a conventional soil sampling of 30 soil samples for each field to quantify their accuracy level. Although of limited extent and with a specific focus, the low average errors (Clay ± 2.71%, OM ± 0.16%) we obtained using only three soil samples suggest a wider potential for this methodology. The proposed approach, integrating S2 data and traditional soil-sampling methods could considerably reduce soil-sampling time and costs in ordinary and precision agriculture applications.
Safe Hb Concentration Measurement during Bladder Irrigation Using Artificial Intelligence
Authors: Reis Gerd , Tan Xiaoying , Kraft Lea , Yilmaz Mehmet , Schoeb Dominik Stephan , Miernik Arkadiusz
Published: August 2021

We have developed a sensor for monitoring the hemoglobin (Hb) concentration in the effluent of a continuous bladder irrigation. The Hb concentration measurement is based on light absorption within a fixed measuring distance. The light frequency used is selected so that both arterial and venous Hb are equally detected. The sensor allows the measurement of the Hb concentration up to a maximum value of 3.2 g/dL (equivalent to ≈20% blood concentration). Since bubble formation in the outflow tract cannot be avoided with current irrigation systems, a neural network is implemented that can robustly detect air bubbles within the measurement section. The network considers both optical and temporal features and is able to effectively safeguard the measurement process. The sensor supports the use of different irrigants (salt and electrolyte-free solutions) as well as measurement through glass shielding. The sensor can be used in a non-invasive way with current irrigation systems. The sensor is positively tested in a clinical study.
Analysis and Improvement of Indoor Positioning Accuracy for UWB Sensors
Authors: Yao Leehter , Yao Lei , Wu Yeong-Wei
Published: August 2021

Ultra-wideband (UWB) sensors have been widely applied to indoor positioning. The indoor positioning of UWB sensors usually refers to the positioning of the mobile node that interacts with the anchors through radio for calculating the distance between the mobile node and each of the surrounding anchors. The positioning accuracy of the mobile node is affected by the installation positions of surrounding anchors. A mathematical model was proposed in this paper to respectively analyze the mobile node’s 2-dimensional (2D) and 3-dimensional (3D) positioning errors. The factors influencing the mobile node’s positioning errors were explored through the mathematical models. The best installation positions of surrounding anchors were obtained based on the mathematical models. The mobile node’s 2D and 3D positioning errors were reduced based on the anchor positions derived from the mathematical model. Both computer simulations and practical experiments were implemented to justify the results obtained in the mathematical models.
Impact of Drought and Changing Water Sources on Water Use and Soil Salinity of Almond and Pistachio Orchards: 1. Observations
Authors: Helalia Sarah A. , Anderson Ray G. , Skaggs Todd H. , Jenerette G. Darrel , Wang Dong , Šimůnek Jirka
Published: August 2021

Soil salinity increases when growers are forced to use higher salinity irrigation waters due to water shortages. It is necessary to estimate the impact of irrigation water on soil properties and conditions for crop growth to manage the effects of salinity on perennial crops. Therefore, in this study, we monitored root zone salinity in five almond and pistachio orchards in eastern and western San Joaquin Valley (SJV), California (CA). Volumetric soil water contents and bulk electrical conductivities were measured at four root-zone depths. Evapotranspiration was measured by eddy covariance along with three other types of data. The first is seasonal precipitation and irrigation patterns, including the temporal distribution of rains, irrigation events, and irrigation water salinity. The second is soil chemistry, including the initial sodium adsorption ratio (SAR) and soil solute electrical conductivity (ECe). The third type is the physical properties, including soil type, hydraulic conductivity, and bulk density. As expected, we found low salinity at the eastern sites and higher salinity at the western sites. The western sites have finer textured soils and lower quality irrigation water; measured actual ET was about 90% of modeled crop ET. Across the three western sites, the annual average apparent leaching fraction ranged from 11 to 28%. At the eastern sites, measured ET almost exactly matched modeled crop ET each year. Apparent leaching fractions in the eastern sites were approximately 20%.
Study on Landscape Ecological Classification and Landscape Types Evolution: A Case Study of a Mining City in Semi-Arid Steppe
Authors: Wu Zhenhua , Lu Qingqing , Lei Shaogang , Yan Qingwu
Published: August 2021

Landscape Ecological Classification (LEC) is the premise and foundation of landscape ecology research. The current research on LEC of Mining Cities in the Semi-arid Steppe (MCSS) is relatively low. Moreover, the question of how to classify the mining landscape into ecologically significant landscape units at a scale suitable for ecological management has not been clear. The research results are as follows: (1) Google Earth, Gaode map, Baidu map, various high-resolution images, unmanned aerial vehicle, and field investigation were used to investigate the landscape types. Based on the land classification of the occurrence model, integrating theories of landscape ecology, mining, ecology, geography, and land resources, this study constructed the LEC system for MCSS using the top-down decomposition classification method, including 4 types of landscape kingdom, 16 types of landscape class, 62 types of landscape family, and more than 200 types of landscape species. (2) Based on LEC, we found the landscape type evolution characteristics of MCSS. Both the open-pit landscape and the dumping landscape were constantly expanding, and ecological restoration of the mining area was carried out simultaneously with coal mining. The trend of Change Intensity (CI) of mining industrial square landscape and industrial storage landscape was very similar. The development of coal has driven the development of the regional industry. The expansion intensity of the town commercial and residential service landscape was gradually decreasing, and the motivation for town expansion was insufficient. The research area was a typical landscape evolution mode of “human advance and grassland retreat”. However, the intensity of humans occupying grassland was decreasing. This study provides a reference for the research of LEC in the semi-arid steppe and provides a theoretical basis for the landscape ecological assessment, planning, and management of mining cities.
A Stability Improvement Method of DC Microgrid System Using Passive Damping and Proportional-Resonance (PR) Control
Authors: Lee Jae-Suk , Choi Yeong-Jun
Published: August 2021

Sustainable energy, such as sunlight and wind energy, that comes from sources that do not need to be replenished has become important. Accordingly, the importance of the design and stable management of DC microgrids is also increasing. From this point of view, this paper analyzes the interaction between source and load converters constituting the DC microgrid using the derived mathematical input and output impedances models. This paper proposes a stability improvement method using the analyzed result. The method focuses on the presence or absence of input and output impedance overlap using Middlebrook’s stability criteria. To verify validity of the proposed method, a case study with three damping methods is conducted: (1) RC parallel damping with PR controller, (2) RL parallel damping with PR controller, and (3) RL series damping with PR controller. Additionally, the frequency domain characteristics and the Nyquist stability are analyzed using MATLAB, and simulation verification is conducted using PSIM. Through the analysis and simulation results, we confirm that the stability of the DC microgrid can be improved by applying the proposed method. The passive damping method analyzed in this paper is applied to an installed power converter, where it is possible to ensure the stability of the DC microgrid.
Role of Industry 4.0 in Supply Chains Sustainability: A Systematic Literature Review
Authors: Naseem Muhammad Hamza , Yang Jiaqi
Published: August 2021

Industry 4.0 and supply chain 4.0 are hot topics in the current business and technological era. This paper provides a literature review, past and current insights, and knowledge of supply chain 4.0 and Industry 4.0 in the context of sustainability. Literature shows that Industry 4.0 has a significant impact on the sustainability of the supply chain network. This paper also explains the different technologies of Industry 4.0, contributing to the sustainability of the supply chain in business. A total of 55 papers are reviewed in this study. We proposed a framework that identifies the effect of Industry 4.0 technologies on the supply chain. This research study used the systematic literature review methodology in Industry 4.0 and supply chain sustainability. The data was collected from (ScienceDirect, IEEE Xplore, and Google Scholar) databases. The Prisma framework was used to select articles for this study and only journal papers were selected for reviewing the literature. This study’s uniqueness concerns its integration of the two independent subjects (Industry 4.0 and supply chain sustainability) to develop the framework explaining the effects of the technologies of Industry 4.0 on supply chain sustainability. Moreover, this research extends the existing knowledge of current fields.