bluuebunny/crossref_metadata_2025 huggingface dataset:
A Deeper Microscopic Study of the Interaction between Gum Rosin Derivatives and a Mater-Bi Type Bioplastic
Authors: Aldas Miguel , Rayón Emilio , López-Martínez Juan , Arrieta Marina P.
Published: January 2020

The interaction between gum rosin and gum rosin derivatives with Mater-Bi type bioplastic, a biodegradable and compostable commercial bioplastic, were studied. Gum rosin and two pentaerythritol esters of gum rosin (Lurefor 125 resin and Unik Tack P100 resin) were assessed as sustainable compatibilizers for the components of Mater-Bi® NF 866 polymeric matrix. To study the influence of each additive in the polymeric matrix, each gum rosin-based additive was compounded in 15 wt % by melt-extrusion and further injection molding process. Then, the mechanical properties were assessed, and the tensile properties and impact resistance were determined. Microscopic analyses were carried out by field emission scanning electron microscopy (FE-SEM), atomic force microscopy (AFM) and atomic force microscopy with nanomechanical assessment (AFM-QNM). The oxygen barrier and wettability properties were also assayed. The study revealed that the commercial thermoplastic starch is mainly composed of three phases: A polybutylene adipate-co-terephthalate (PBAT) phase, an amorphous phase of thermoplastic starch (TPSa), and a semi-crystalline phase of thermoplastic starch (TPSc). The poor miscibility among the components of the Mater-Bi type bioplastic was confirmed. Finally, the formulations with the gum rosin and its derivatives showed an improvement of the miscibility and the solubility of the components depending on the additive used.
Correction: Duan, G.J., et al. The Poly(acrylonitrule-co-acrylic acid)-graft-β-cyclodextrin Hydrogel for Thorium(IV) Adsorption. Polymers 2017, 9, 201
Authors: Duan Guojian , Zhong Qiangqiang , Bi Lei , Yang Liu , Liu Tonghuan , Shi Xiaoning , Wu Wangsuo
Published: January 2020

The authors wish to make the following corrections to their paper [...]
New Eco-Friendly Synthesized Thermosets from Isoeugenol-Based Epoxy Resins
Authors: Ruiz Quentin , Pourchet Sylvie , Placet Vincent , Plasseraud Laurent , Boni Gilles
Published: January 2020

Epoxy resin plays a key role in composite matrices and DGEBA is the major precursor used. With the aim of favouring the use of bio resources, epoxy resins can be prepared from lignin. In particular, diglycidyl ether of isoeugenol derivatives are good candidates for the replacement of DGEBA. This article presents an effective and eco-friendly way to prepare epoxy resin derived from isoeugenol (BioIgenox), making its upscale possible. BioIgenox has been totally characterized by NMR, FTIR, MS and elemental analyses. Curing of BioIgenox and camphoric anhydride with varying epoxide function/anhydride molar ratios has allowed determining an optimum ratio near 1/0.9 based on DMA and DSC analyses and swelling behaviours. This thermoset exhibits a Tg measured by DMA of 165 °C, a tensile storage modulus at 40 °C of 2.2 GPa and mean 3-point bending stiffness, strength and strain at failure of 3.2 GPa, 120 MPa and 6.6%, respectively. Transposed to BioIgenox/hexahydrophtalic anhydride, this optimized formulation gives a thermoset with a Tg determined by DMA of 140 °C and a storage modulus at 40 °C of 2.6 GPa. The thermal and mechanical properties of these two thermosets are consistent with their use as matrices for structural or semi-structural composites.
Nanolayers of Poly(N,N′-Dimethylaminoethyl Methacrylate) with a Star Topology and Their Antibacterial Activity
Authors: Teper Paulina , Chojniak-Gronek Joanna , Hercog Anna , Oleszko-Torbus Natalia , Płaza Grażyna , Kubacki Jerzy , Balin Katarzyna , Kowalczuk Agnieszka , Mendrek Barbara
Published: January 2020

In this paper, we focus on the synthesis and characterization of novel stable nanolayers made of star methacrylate polymers. The effect of nanolayer modification on its antibacterial properties was also studied. A covalent immobilization of star poly(N,N′-dimethylaminoethyl methacrylate) (PDMAEMA) to benzophenone functionalized glass or silicon supports was carried out via a “grafting to” approach using UV irradiation. To date, star polymer UV immobilization has never been used for this purpose. The thickness of the resulting nanolayers increased from 30 to 120 nm with the molar mass of the immobilized stars. The successful bonding of star PDMAEMA to the supports was confirmed by surface sensitive quantitative spectroscopic methods. Next, amino groups in the polymer layer were quaternized with bromoethane, and the influence of this modification on the antibacterial properties of the obtained materials was analyzed using a selected reference strain of bacteria. The resulting star nanolayer surfaces exhibited higher antimicrobial activity against Bacillus subtilis ATCC 6633 compared to that of the linear PDMAEMA analogues grafted onto a support. These promising results and the knowledge about the influence of the topology and modification of PDMAEMA layers on their properties may help in searching for new materials for antimicrobial applications in medicine.
Poly(d,l-Lactic acid) Composite Foams Containing Phosphate Glass Particles Produced via Solid-State Foaming Using CO2 for Bone Tissue Engineering Applications
Authors: Shah Mohammadi Maziar , Rezabeigi Ehsan , Bertram Jason , Marelli Benedetto , Gendron Richard , Nazhat Showan N. , Bureau Martin N.
Published: January 2020

This study reports on the production and characterization of highly porous (up to 91%) composite foams for potential bone tissue engineering (BTE) applications. A calcium phosphate-based glass particulate (PGP) filler of the formulation 50P2O5-40CaO-10TiO2 mol.%, was incorporated into biodegradable poly(d,l-lactic acid) (PDLLA) at 5, 10, 20, and 30 vol.%. The composites were fabricated by melt compounding (extrusion) and compression molding, and converted into porous structures through solid-state foaming (SSF) using high-pressure gaseous carbon dioxide. The morphological and mechanical properties of neat PDLLA and composites in both nonporous and porous states were examined. Scanning electron microscopy micrographs showed that the PGPs were well dispersed throughout the matrices. The highly porous composite systems exhibited improved compressive strength and Young’s modulus (up to >2-fold) and well-interconnected macropores (up to ~78% open pores at 30 vol.% PGP) compared to those of the neat PDLLA foam. The pore size of the composite foams decreased with increasing PGPs content from an average of 920 µm for neat PDLLA foam to 190 µm for PDLLA-30PGP. Furthermore, the experimental data was in line with the Gibson and Ashby model, and effective microstructural changes were confirmed to occur upon 30 vol.% PGP incorporation. Interestingly, the SSF technique allowed for a high incorporation of bioactive particles (up to 30 vol.%—equivalent to ~46 wt.%) while maintaining the morphological and mechanical criteria required for BTE scaffolds. Based on the results, the SSF technique can offer more advantages and flexibility for designing composite foams with tunable characteristics compared to other methods used for the fabrication of BTE scaffolds.
Narrowband Spontaneous Emission Amplification from a Conjugated Oligomer Thin Film
Authors: AlSalhi Mohamad S. , Aljaafreh Mamduh J. , Prasad Saradh
Published: January 2020

In this paper, we studied the laser and optical properties of conjugated oligomer (CO) 1,4-bis(9-ethyl-3-carbazo-vinylene)-9,9-dihexyl-fluorene (BECV-DHF) thin films, which were cast onto a quartz substrate using a spin coating technique. BECV-DHF was dissolved in chloroform at different concentrations to produce thin films with various thicknesses. The obtained results from the absorption spectrum revealed one sharp peak at 403 nm and two broads at 375 and 428 nm. The photoluminescence (PL) spectra were recorded for different thin films made from different concentrations of the oligomer solution. The threshold, laser-induced fluorescence (LIF), and amplified spontaneous emission (ASE) properties of the CO BECV-DHF thin films were studied in detail. The ASE spectrum was achieved at approximately 482.5 nm at a suitable concentration and sufficient pump energy. The time-resolved spectroscopy of the BECV-DHF films was demonstrated at different pump energies.
Plasmonic-Active Nanostructured Thin Films
Authors: Bhattarai Jay K. , Maruf Md Helal Uddin , Stine Keith J.
Published: January 2020

Plasmonic-active nanomaterials are of high interest to scientists because of their expanding applications in the field for medicine and energy. Chemical and biological sensors based on plasmonic nanomaterials are well-established and commercially available, but the role of plasmonic nanomaterials on photothermal therapeutics, solar cells, super-resolution imaging, organic synthesis, etc. is still emerging. The effectiveness of the plasmonic materials on these technologies depends on their stability and sensitivity. Preparing plasmonics-active nanostructured thin films (PANTFs) on a solid substrate improves their physical stability. More importantly, the surface plasmons of thin film and that of nanostructures can couple in PANTFs enhancing the sensitivity. A PANTF can be used as a transducer for any of the three plasmonic-based sensing techniques, namely, the propagating surface plasmon, localized surface plasmon resonance, and surface-enhanced Raman spectroscopy-based sensing techniques. Additionally, continuous nanostructured metal films have an advantage for implementing electrical controls such as simultaneous sensing using both plasmonic and electrochemical techniques. Although research and development on PANTFs have been rapidly advancing, very few reviews on synthetic methods have been published. In this review, we provide some fundamental and practical aspects of plasmonics along with the recent advances in PANTFs synthesis, focusing on the advantages and shortcomings of the fabrication techniques. We also provide an overview of different types of PANTFs and their sensitivity for biosensing.
Correlation between Antibacterial Activity and Free-Radical Scavenging: In-Vitro Evaluation of Polar/Non-Polar Extracts from 25 Plants
Authors: Rayan Mahmoud , Abu-Farich Baheer , Basha Walid , Rayan Anwar , Abu-Lafi Saleh
Published: January 2020

Objectives: The current study aimed to measure the antioxidant and antibacterial activities of 25 wild Palestinian edible plants, which were subjected to extraction by polar and non-polar solvents. Correlations between free radical scavenging activity and antibacterial activity of the extracts were assessed for both polar and non-polar fractions. Materials: Twenty-five wild edible plant species that are frequently consumed by people in Palestine (mainly in a rural area) were examined. Among them, 10 plant species were among those with the highest mean cultural importance values, according to an ethnobotanical survey that was conducted in the West Bank, Palestine, a few years ago. Method: The protocol of the DPPH assay for testing free-radical scavenging was utilized for determining EC50 values, while microdilution tests were conducted to determine the 50% inhibitory concentration (IC50) of the extracts for the microorganism Staphylococcus mutans. Results and Discussion: Eight extracts (non-polar fractions) were found to possess an antibacterial IC50 of less than 20 ppm, such as Foeniculum vulgare, Salvia palaestinafruticose, Micromeria fruticose, Trigonella foenum-graecum, Cichorium pumilum jacq, Salvia hierosolymitana boiss, Ruta chalepensis, and Chrysanthemum coronarium. The polar fractions possess higher antioxidant activity, while non-polar fraction possess higher antibacterial activity. Looking at all the results together can deceive and lead to the conclusion that there is no correlation between antibacterial activity against S. mutans and free radical scavenging (R2 equals 0.0538). However, in-depth analysis revealed that non-polar plant extracts with an EC50 of free radical scavenging ≤100 ppm have a four-fold order of enrichment toward more activity against S. mutans. These findings are of high importance for screening projects. A four-fold order of enrichment could save plenty of time and many in screening projects. The antibacterial active extracts marked by low-medium free radical scavenging might act through a mechanism of action other than that of highly active, free radical scavenging extracts. Conclusion: The screening of antioxidant and antimicrobial activity performed on 25 selected wild plant extracts revealed a satisfactory free radical scavenging and antimicrobial potential that could be of value in the management of oxidative stress. Further studies are recommended to explore novel and highly active natural antibacterial products.
Energy and Material Flows and Carbon Footprint Assessment Concerning the Production of HMF and Furfural from a Cellulosic Biomass
Authors: Schöppe Hannes , Kleine-Möllhoff Peter , Epple Rolf
Published: January 2020

5-hydroxymethyl-furfural (HMF) and furfural are interesting as potential platform chemicals for a bio-based chemical production economy. Within the scope of this work, the process routes under technical development for the production of these platform chemicals were investigated. For two selected processes, the material and energy flows, as well as the carbon footprint, were examined in detail. The possible production process optimizations, further development potentials, and the research demand against the background of the reduction of the primary energy expenditure were worked out.
Estimating the Generation of Garden Waste in England and the Differences between Rural and Urban Areas
Authors: Eades Paul , Kusch-Brandt Sigrid , Heaven Sonia , Banks Charles J.
Published: January 2020

Garden waste arising from private households represents a major component of the biodegradable municipal waste stream. To design effective waste valorisation schemes, detailed information about garden waste is a prerequisite. While the biochemical composition of this material is well documented, there is a lack of knowledge regarding both the quantities arising, and quantities entering the services operated by waste management authorities. This work studied the quantities of garden waste arisings at urban and rural households along with the disposal methods used. A door-to-door interview survey, an analysis of kerbside collections of garden waste, and an assessment of materials brought by citizens to a waste recycling site were carried out in Hampshire, UK. If extrapolated nationally, the results indicate that households in England produce an average of 0.79 kg of garden waste per day, or 288 kg per year. On a per capita basis, this corresponds to an annual arising of 120 kg per person, out of which around 70% enters the collection schemes of the waste management authorities. The quantity generated by rural and urban households differed substantially, with rural households producing 1.96 ± 1.35 kg per day and urban households 0.64 ± 0.46 kg per day. Rural households adopted self-sufficient methods of garden waste management such as home composting or backyard burning to a much greater extent compared with urban households. Less than half of the generated rural garden waste entered services operated by the waste collection authorities, while urban households strongly relied on these services. A detailed breakdown of the disposal routes chosen by urban and rural householders can support authorities in tailoring more effective waste management schemes.
Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations
Authors: Koike Takaaki , Hofert Marius
Published: January 2020

In this paper, we propose a novel framework for estimating systemic risk measures and risk allocations based on Markov Chain Monte Carlo (MCMC) methods. We consider a class of allocations whose jth component can be written as some risk measure of the jth conditional marginal loss distribution given the so-called crisis event. By considering a crisis event as an intersection of linear constraints, this class of allocations covers, for example, conditional Value-at-Risk (CoVaR), conditional expected shortfall (CoES), VaR contributions, and range VaR (RVaR) contributions as special cases. For this class of allocations, analytical calculations are rarely available, and numerical computations based on Monte Carlo (MC) methods often provide inefficient estimates due to the rare-event character of the crisis events. We propose an MCMC estimator constructed from a sample path of a Markov chain whose stationary distribution is the conditional distribution given the crisis event. Efficient constructions of Markov chains, such as the Hamiltonian Monte Carlo and Gibbs sampler, are suggested and studied depending on the crisis event and the underlying loss distribution. The efficiency of the MCMC estimators is demonstrated in a series of numerical experiments.
Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion
Authors: Annala Leevi , Honkavaara Eija , Tuominen Sakari , Pölönen Ilkka
Published: January 2020

Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation health. The objective of this study was to develop a novel approach for retrieving chlorophyll a and b values from remotely sensed data by inverting the stochastic model of leaf optical properties using a one-dimensional convolutional neural network. The inversion results and retrieved values are validated in two ways: A classical machine learning validation dataset and calculating chlorophyll maps from empirical remotely sensed hyperspectral data and comparing them to TCARI OSAVI , an index that has strong negative correlation with chlorophyll concentration. With the validation dataset, coefficients of determination ( R 2 ) of 0.97 were obtained for chlorophyll a and 0.95 for chlorophyll b. The chlorophyll maps correlate with the TCARI OSAVI map. The correlation coefficient (R) is −0.87 for chlorophyll a and −0.68 for chlorophyll b in selected plots. These results indicate that the approach is highly promising approach for estimating vegetation chlorophyll content.
Investigation of Tightly Combined Single-Frequency and Single-Epoch Precise Positioning Using Multi-GNSS Data
Authors: Deng Chenlong , Liu Qian , Zou Xuan , Tang Weiming , Cui Jianhui , Wang Yawei , Guo Chi
Published: January 2020

The loose combination (LC) and the tight combination (TC) are two different models in the combined processing of four global navigation satellite systems (GNSSs). The former is easy to implement but may be unusable with few satellites, while the latter should cope with the inter-system bias (ISB) and is applicable for few tracked satellites. Furthermore, in both models, the inter-frequency bias (IFB) in the GLObal NAvigation Satellite System (GLONASS) system should also be removed. In this study, we aimed to investigate the performance difference of ambiguity resolution and position estimation between these two models simultaneously using the single-frequency data of all four systems (GPS + GLONASS + Galileo + BeiDou Navigation Satellite System (BDS)) in three different environments, i.e., in an open area, with surrounding high buildings, and under a block of high buildings. For this purpose, we first provide the definition of ISB and IFB from the perspective of the hardware delays, and then propose practical algorithms to estimate the IFB rate and ISB. Thereafter, a comprehensive performance comparison was made between the TC and LC models. Experiments were conducted to simulate the above three observation environments: the typical situation and situations suffering from signal obstruction with high elevation angles and limited azimuths, respectively. The results show that in a typical situation, the TC and LC models achieve a similar performance. However, when the satellite signals are severely obstructed and few satellites are tracked, the float solution and ambiguity fixing rates in the LC model are dramatically decreased, while in the TC model, there are only minor declines and the difference in the ambiguity fixing rates can be as large as 30%. The correctly fixed ambiguity rates in the TC model also had an improvement of around 10%. Once the ambiguity was fixed, both models achieved a similar positioning accuracy.
Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato
Authors: Gold Kaitlin M. , Townsend Philip A. , Chlus Adam , Herrmann Ittai , Couture John J. , Larson Eric R. , Gevens Amanda J.
Published: January 2020

In-vivo foliar spectroscopy, also known as contact hyperspectral reflectance, enables rapid and non-destructive characterization of plant physiological status. This can be used to assess pathogen impact on plant condition both prior to and after visual symptoms appear. Challenging this capacity is the fact that dead tissue yields relatively consistent changes in leaf optical properties, negatively impacting our ability to distinguish causal pathogen identity. Here, we used in-situ spectroscopy to detect and differentiate Phytophthora infestans (late blight) and Alternaria solani (early blight) on potato foliage over the course of disease development and explored non-destructive characterization of contrasting disease physiology. Phytophthora infestans, a hemibiotrophic pathogen, undergoes an obligate latent period of two–seven days before disease symptoms appear. In contrast, A. solani, a necrotrophic pathogen, causes symptoms to appear almost immediately when environmental conditions are conducive. We found that respective patterns of spectral change can be related to these differences in underlying disease physiology and their contrasting pathogen lifestyles. Hyperspectral measurements could distinguish both P. infestans-infected and A. solani-infected plants with greater than 80% accuracy two–four days before visible symptoms appeared. Individual disease development stages for each pathogen could be differentiated from respective controls with 89–95% accuracy. Notably, we could distinguish latent P. infestans infection from both latent and symptomatic A. solani infection with greater than 75% accuracy. Spectral features important for late blight detection shifted over the course of infection, whereas spectral features important for early blight detection remained consistent, reflecting their different respective pathogen biologies. Shortwave infrared wavelengths were important for differentiation between healthy and diseased, and between pathogen infections, both pre- and post-symptomatically. This proof-of-concept work supports the use of spectroscopic systems as precision agriculture tools for rapid and early disease detection and differentiation tools, and highlights the importance of careful consideration of underlying pathogen biology and disease physiology for crop disease remote sensing.
Verification of Accuracy of Unmanned Aerial Vehicle (UAV) Land Surface Temperature Images Using In-Situ Data
Authors: Song Bonggeun , Park Kyunghun
Published: January 2020

The accuracy of land surface temperatures (LSTs) acquired by an unmanned aerial vehicle (UAV) was verified by comparison with in-situ LSTs of various land cover materials at the Changwon National University Campus, Changwon City, South Korea. UAV imaging and in-situ measurements were performed on 31 July and 2 August 2019. During the in-situ measurements, LST was measured at 160 points using an infrared thermometer. The linear regression model between the UAV and in-situ measurements exhibited a very high correlation on both days, with R2 values greater than 0.7004. The root mean square error (RMSE), however, was 4.030 °C on 31 July and 5.446 °C on 2 August and it also varied depending on the land cover type. These results may depend on various factors, such as the field of view and performance of the TIR (Thermal infrared radiance) camera, as well as the weather and atmospheric conditions. Accurately diagnosing the thermal characteristics of urban areas based on the spatial elements can be used to accurately analyze the thermal characteristics of urban areas and to make effective policy decisions. Techniques for verifying and improving the accuracy of UAV TIR LST data for various land cover materials are required to enable precise investigation of the thermal characteristics of urban areas.
Precipitation Regime Classification Based on Cloud-Top Temperature Time Series for Spatially-Varied Parameterization of Precipitation Models
Authors: Lu Sha , ten Veldhuis Marie-claire , van de Giesen Nick , Heemink Arnold , Verlaan Martin
Published: January 2020

Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delineation boundaries of precipitation regimes should be accurately identified. Existing approaches to characterize precipitation regimes by seasonal or other climatological properties do not account for small scale spatial-temporal variability. Precipitation time series can be used to account for this small-scale variability in regime classification. Unfortunately, precipitation products with global coverage perform poorly at small time scales over data scarce regions. A methodology of using satellite-based cloud-top temperature (CTT) time series as a proxy of precipitation time series for precipitation regime classification was developed, and its potential and uncertainty were analyzed. A precipitation regime in this study was defined on the basis of characteristic small-scale temporal distribution and variability of precipitation at a given place. Dynamic time warping was used to calculate the distance between two time series. Criteria to select the optimal temporal scale of time series for clustering and the number of clusters were also developed. The method was validated over Germany and applied to Tanzania, characterized by complex climatology and low density ground observations. This approach was evaluated against precipitation regime classification based on a satellite precipitation product. Results show that CTT outcompetes satellite-based precipitation for classification of precipitation regime classification. The CTT-based classification can be used as precursor to spatially adapted precipitation estimation algorithms where parameters are calibrated by gauge data or other ground-based precipitation observations, and parameterization can be used for satellite-precipitation estimates, precipitation forecasts in numerical or stochastic weather models, etc.
Insar Maps of Land Subsidence and Sea Level Scenarios to Quantify the Flood Inundation Risk in Coastal Cities: The Case of Singapore
Authors: Catalao Joao , Raju Durairaju , Nico Giovanni
Published: January 2020

Global mean sea level rise associated with global warming has a major impact on coastal areas and represents one of the significant natural hazards. The Asia-Pacific region, which has the highest concentration of human population in the world, represents one of the larger areas on Earth being threatened by the rise of sea level. Recent studies indicate a global sea level of 3.2 mm/yr as measured from 20 years of satellite altimetry. The combined effect of sea level rise and local land subsidence, can be overwhelming for coastal areas. The Synthetic Aperture Radar (SAR) interferometry technique is used to process a time series of TerraSAR-X images and estimate the land subsidence in the urban area of Singapore. Interferometric SAR (InSAR) measurements are merged to the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 sea-level rise scenarios to identify projected inundated areas and provide a map of flood vulnerability. Subsiding rates larger than 5 mm/year are found near the shore on the low flat land, associated to areas recently reclaimed or built. The projected flooded map of Singapore are provided for different sea-level rise scenarios. In this study, we show that local land subsidence can increase the flood vulnerability caused by sea level rise by 2100 projections. This can represent an increase of 25% in the flood area in the central area of Singapore for the RCP4.5 scenario.
Understanding Land Subsidence Along the Coastal Areas of Guangdong, China, by Analyzing Multi-Track MTInSAR Data
Authors: Du Yanan , Feng Guangcai , Liu Lin , Fu Haiqiang , Peng Xing , Wen Debao
Published: January 2020

Coastal areas are usually densely populated, economically developed, ecologically dense, and subject to a phenomenon that is becoming increasingly serious, land subsidence. Land subsidence can accelerate the increase in relative sea level, lead to a series of potential hazards, and threaten the stability of the ecological environment and human lives. In this paper, we adopted two commonly used multi-temporal interferometric synthetic aperture radar (MTInSAR) techniques, Small baseline subset (SBAS) and Temporarily coherent point (TCP) InSAR, to monitor the land subsidence along the entire coastline of Guangdong Province. The long-wavelength L-band ALOS/PALSAR-1 dataset collected from 2007 to 2011 is used to generate the average deformation velocity and deformation time series. Linear subsidence rates over 150 mm/yr are observed in the Chaoshan Plain. The spatiotemporal characteristics are analyzed and then compared with land use and geology to infer potential causes of the land subsidence. The results show that (1) subsidence with notable rates (>20 mm/yr) mainly occurs in areas of aquaculture, followed by urban, agricultural, and forest areas, with percentages of 40.8%, 37.1%, 21.5%, and 0.6%, respectively; (2) subsidence is mainly concentrated in the compressible Holocene deposits, and clearly associated with the thickness of the deposits; and (3) groundwater exploitation for aquaculture and agricultural use outside city areas is probably the main cause of subsidence along these coastal areas.
Advanced Machine Learning and Big Data Analytics in Remote Sensing for Natural Hazards Management
Authors: Martínez-Álvarez Francisco , Tien Bui Dieu
Published: January 2020

This editorial summarizes the performance of the special issue entitled Advanced Machine Learning and Big Data Analytics in Remote Sensing for Natural Hazards Management, which was published at MDPI’s Remote Sensing journal. The special issue took place in years 2018 and 2019 and accepted a total of nine papers from authors of thirteen different countries. So far, these papers have dealt with 116 cites. Earthquakes, landslides, floods, wildfire and soil salinity were the topics analyzed. New methods were introduced, with applications of the utmost relevance.
An Adaptive Hierarchical Detection Method for Ship Targets in High-Resolution SAR Images
Authors: Liang Yi , Sun Kun , Zeng Yugui , Li Guofei , Xing Mengdao
Published: January 2020

With the improvement of image resolution in synthetic aperture radars (SARs), sea clutter characteristics become more complex, which poses new challenges to traditional ship target detection missions. In this paper, to detect ship targets quickly and efficiently in a complex background, we propose an adaptive hierarchical detection method based on a coarse-to-fine mechanism. This method constructs a new visual attention mechanism to strengthen ship targets and obtain the candidate targets adaptively by the means dichotomy method. On this basis, the precise detection results of the targets are obtained using the speed block kernel density estimation method, which maintains constant false alarm characteristics. Compared with existing methods, the adaptive hierarchical detection method has simple, fast, and accurate characteristics. Experiments based on GF-III satellite and airborne SAR datasets are presented to demonstrate the effectiveness of the proposed method.
Advantages of Uncombined Precise Point Positioning with Fixed Ambiguity Resolution for Slant Total Electron Content (STEC) and Differential Code Bias (DCB) Estimation
Authors: Wang Jin , Huang Guanwen , Zhou Peiyuan , Yang Yuanxi , Zhang Qin , Gao Yang
Published: January 2020

The determination of slant total electron content (STEC) between satellites and receivers is the first step for establishing an ionospheric model. However, the leveling errors, caused by the smoothed ambiguity solutions in the carrier-to-code leveling (CCL) method, degrade the performance of ionosphere modeling and differential code bias (DCB) estimation. To reduce the leveling errors, an uncombined and undifferenced precise point positioning (PPP) method with ambiguity resolution (AR) was used to directly extract the STEC. Firstly, the ionospheric observables were estimated with CCL, PPP float-ambiguity solutions, and PPP fixed-ambiguity solutions, respectively, to analyze the short-term temporal variation of receiver DCB in zero or short baselines. Then, the global ionospheric map (GIM) was modeled using three types of ionospheric observables based on the single-layer model (SLM) assumption. Compared with the CCL method, the slight variations of receiver DCBs can be obviously distinguished using high precise ionospheric observables, with a 58.4% and 71.2% improvement of the standard deviation (STD) for PPP float-ambiguity and fixed-ambiguity solutions, respectively. For ionosphere modeling, the 24.7% and 27.9% improvements for posteriori residuals were achieved for PPP float-ambiguity and fixed-ambiguity solutions, compared to the CCL method. The corresponding improvement for residuals of the vertical total electron contents (VTECs) compared with the Center for Orbit Determination in Europe (CODE) final GIM products in global accuracy was 9.2% and 13.7% for PPP float-ambiguity and fixed-ambiguity solutions, respectively. The results show that the PPP fixed-ambiguity solution is the best one for the GIM product modeling and satellite DCBs estimation.
A Mobile LiDAR for Monitoring Mechanically Stabilized Earth Walls with Textured Precast Concrete Panels
Authors: Aldosari Mohammed , Al-Rawabdeh Abdulla , Bullock Darcy , Habib Ayman
Published: January 2020

Mechanically Stabilized Earth (MSE) walls retain soil on steep, unstable slopes with crest loads. Over the last decade, they are becoming quite popular due to their high cost-to-benefit ratio, design flexibility, and ease of construction. Like any civil infrastructure, MSE walls need to be continuously monitored according to transportation asset management criteria during and after the construction stage to ensure that their expected serviceability measures are met and to detect design and/or construction issues, which could lead to structural failure. Current approaches for monitoring MSE walls are mostly qualitative (e.g., visual inspection or examination). Besides being time consuming, visual inspection might have inconsistencies due to human subjectivity. This research focuses on a comprehensive strategy using a mobile LiDAR mapping System (MLS) for the acquisition and processing of point clouds covering the MSE wall. The processing strategy delivers a set of global and local performance measure for MSE walls. Moreover, it is also capable of handling MSE walls with smooth or textured panels with the latter being the focus of this research due to its more challenging nature. For this study, an ultra-high-accuracy wheel-based MLS has been developed to efficiently acquire reliable data conducive to the development of the serviceability measures. To illustrate the feasibility of the proposed acquisition/processing strategy, two case studies in this research have been conducted with the first one focusing on the comparative performance of static and mobile LiDAR in terms of the agreement of the derived serviceability measures. The second case study aims at illustrating the feasibility of the proposed strategy in handling large textured MSE walls. Results from both case studies confirm the potential of using MLS for efficient, economic, and reliable monitoring of MSE walls.
Impacts of Land Cover/Use on the Urban Thermal Environment: A Comparative Study of 10 Megacities in China
Authors: Liu Fei , Zhang Xinmin , Murayama Yuji , Morimoto Takehiro
Published: January 2020

Satellite-derived land surface temperature (LST) reveals the variations and impacts on the terrestrial thermal environment on a broad spatial scale. The drastic growth of urbanization-induced impervious surfaces and the urban population has generated a remarkably increasing influence on the urban thermal environment in China. This research was aimed to investigate land surface temperature (LST) intensity response to urban land cover/use by examining the thermal impact on urban settings in ten Chinese megacities (i.e., Beijing, Dongguan, Guangzhou, Hangzhou, Harbin, Nanjing, Shenyang, Suzhou, Tianjin, and Wuhan). Surface urban heat island (SUHI) footprints were scrutinized and compared by magnitude and extent. The causal mechanism among land cover composition (LCC), population, and SUHI was also identified. Spatial patterns of the thermal environments were identical to those of land cover/use. In addition, most impervious surface materials (greater than 81%) were labeled as heat sources, on the other hand, water and vegetation were functioned as heat sinks. More than 85% of heat budgets in Beijing and Guangzhou were generated from impervious surfaces. SUHI for all megacities showed spatially gradient decays between urban and surrounding rural areas; further, temperature peaks are not always dominant in the urban core, despite extremely dense impervious surfaces. The composition ratio of land cover (LCC%) negatively correlates with SUHI intensity (SUHII), whereas the population positively associates with SUHII. For all targeted megacities, land cover composition and population account for more than 63.9% of SUHI formation using geographically weighted regression. The findings can help optimize land cover/use to relieve pressure from rapid urbanization, maintain urban ecological balance, and meet the demands of sustainable urban growth.
Continuing the MODIS Dark Target Aerosol Time Series with VIIRS
Authors: Sawyer Virginia , Levy Robert C. , Mattoo Shana , Cureton Geoff , Shi Yingxi , Remer Lorraine A.
Published: January 2020

For reflected sunlight observed from space at visible and near-infrared wavelengths, particles suspended in Earth’s atmosphere provide contrast with vegetation or dark water at the surface. This is the physical motivation for the Dark Target (DT) aerosol retrieval algorithm developed for the Moderate Resolution Imaging Spectrometer (MODIS). To extend the data record of aerosol optical depth (AOD) beyond the expected 20-year lifespan of the MODIS sensors, DT must be adapted for other sensors. A version of the DT AOD retrieval for the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar-Orbiting Partnership (SNPP) is now mature enough to be released as a standard data product, and includes some upgraded features from the MODIS version. Differences between MODIS Aqua and VIIRS SNPP lead to some inevitable disagreement between their respective AOD measurements, but the offset between the VIIRS SNPP and MODIS Aqua records is smaller than the offset between those of MODIS Aqua and MODIS Terra. The VIIRS SNPP retrieval shows good agreement with ground-based measurements. For most purposes, DT for VIIRS SNPP is consistent enough and in close enough agreement with MODIS to continue the record of satellite AOD. The reasons for the offset from MODIS Aqua, and its spatial and temporal variability, are investigated in this study.
High-Resolution Reef Bathymetry and Coral Habitat Complexity from Airborne Imaging Spectroscopy
Authors: Asner Gregory P. , Vaughn Nicholas R. , Balzotti Christopher , Brodrick Philip G. , Heckler Joseph
Published: January 2020

Coral reef ecosystems are rapidly changing, and a persistent problem with monitoring changes in reef habitat complexity rests in the spatial resolution and repeatability of measurement techniques. We developed a new approach for high spatial resolution (<1 m) mapping of nearshore bathymetry and three-dimensional habitat complexity (rugosity) using airborne high-fidelity imaging spectroscopy. Using this new method, we mapped coral reef habitat throughout two bays to a maximum depth of 25 m and compared the results to the laser-based SHOALS bathymetry standard. We also compared the results derived from imaging spectroscopy to a more conventional 4-band multispectral dataset. The spectroscopic approach yielded consistent results on repeat flights, despite variability in viewing and solar geometries and sea state conditions. We found that the spectroscopy-based results were comparable to those derived from SHOALS, and they were a major improvement over the multispectral approach. Yet, spectroscopy provided much finer spatial information than that which is available with SHOALS, which is valuable for analyzing changes in benthic composition at the scale of individual coral colonies. Monitoring temporal changes in reef 3D complexity at high spatial resolution will provide an improved means to assess the impacts of climate change and coastal processes that affect reef complexity.
Social and Spatial Experiences in the Cities of Tomorrow
Authors: Giorgi Emanuele , Bugatti Angelo , Bosio Andrea
Published: January 2020

As described by the strong academic literature, (Vattimo, Bauman, Mumford, Simon, Haraway, Meschiari, Florida) the contemporary society is going through new challenges, such as the friction between youth, technology, and productivity. These challenges affect the way people live and experience the cities, but also the way cities need to evolve. An anthological analysis and a study of secondary sources is used to analyze the new spatial and social experiences, while the analysis of Milan (Italy) as a case study of a creative city is used to understand the rapid shift towards the virtualization of cities, in which consumption is progressively induced by a projected image of the city rather than its actual physical fabric. This manuscript opens a research front, with the goal to understand how architecture and urban design should leave the traditional typologies to propose a new way of creating and living architecture, caught in the middle between the real and the virtual.
Sustainable Collaborative Innovation between Research Institutions and Seed Enterprises in China
Authors: Yu Xi , Paudel Krishna P. , Li Dongmei , Xiong Xiaolei , Gong Yanyu
Published: January 2020

Public research institutions are encouraged to engage in industry sustainable collaboration in China. We develop an analytical framework based on the factor-process-outputs model and use a mechanism model by incorporating four elements (innovation climate, strategic partnership, collaborative mechanism, and the degree of participation) associated with the research institutions and industry collaboration. Using data collected from a face-to-face interview survey of 533 experts located at research institutions in seven Chinese provinces and one municipality who have collaborated with the seed industry, we use a structural equation model to identify important factors that affect innovation behavior. Results show that the innovation climate does not directly affect the participation of research institutions in research industry collaboration; however, it has a direct effect on strategic partnership and the collaborative mechanism. We find that an innovation climate could indirectly influence the participation of research institutions via collaborative mechanism and strategic partnership. Furthermore, strategic partnership and collaborative mechanism are found to moderate the participation behavior of research institutions. Moreover, we find that policy support, knowledge innovation strategies, and resource sharing mechanisms are essential factors for sustainable and effective collaboration.
Exploring the Role of Deep Learning Technology in the Sustainable Development of the Music Production Industry
Authors: Weng Sung-Shun , Chen Hung-Chia
Published: January 2020

This study explores the role of deep learning technology in the sustainable development of the music production industry. This article surveys the opinions of Taiwanese music creation professionals and uses partial least squares (PLS) regression to analyze and elucidate the importance of deep learning technology in the music production industry. We found that deep learning cannot replace human creativity, but greater investment in this technology can improve the quality of music creation. In order to achieve sustainable development in the music production industry, industry participants need to awaken consumers’ awareness of music quality, actively enhance the unique value of their art, and strengthen cooperation between industries to provide a friendly environment for listeners.
The Incentives and Efforts for Innovation and Entrepreneurship in a Resource-Based Economy: A Survey on Perspective of Qatari Residents
Authors: Tok Evren
Published: January 2020

This paper studies the local perspective on innovation and entrepreneurship in the resource-based state of Qatar. The effective utilization of abundant natural resources (oil and gas) have propelled the country’s rapid economic development over the last four decades. However, accelerating decarbonization efforts of the global energy system due to climate change put the future value of these hydrocarbon resources into doubt and hence the country’s revenue streams from international trade. Rapidly growing the local population adds further pressure to the social welfare system amid dwindling oil and gas revenues for the state. The argument for economic diversification and theoretical foundations of innovation and entrepreneurship in a resource-rich state are discussed. A survey to measure the attitude of the residents in Qatar towards innovation and state-led initiatives is prepared and conducted with people living in the country. The analysis of the survey shows that Qatari residents are relatively risk-averse and state-dependent in their pursuit of new entrepreneurial opportunities. We identify three possible reasons for such an outcome; they are, (1) the country’s unique economic structure (natural resource-based), (2) demographic structure (expatriates vs. citizens), and (3) lack of previous experience in innovation and entrepreneurship (path dependency) in a relatively young country. The country’s spectacular success in the last three decades has become its Achilles-heel in decoupling the current economy away from hydrocarbon dependence.