bluuebunny/crossref_metadata_2025 huggingface dataset:
Kinetics of Dry-Batch Grinding in a Laboratory-Scale Ball Mill of Sn–Ta–Nb Minerals from the Penouta Mine (Spain)
Authors: Nava Jenniree V. , Llorens Teresa , Menéndez-Aguado Juan María
Published: December 2020

The optimization of processing plants is one of the main concerns in the mining industry, since the comminution stage, a fundamental operation, accounts for up to 70% of total energy consumption. The aim of this study was to determine the effects that ball size and mill speed exert on the milling kinetics over a wide range of particle sizes. This was done through dry milling and batch grinding tests performed on two samples from the Penouta Sn–Ta–Nb mine (Galicia, Spain), and following Austin methodology. In addition, the relationships amongst Sn, Ta and Nb content, as metals of interest, the specific rate of breakage Si, the kinetic parameters, and the operational conditions were studied through X-Ray fluorescence (XRF) techniques. The results show that, overall, the specific rate of breakage Si decreases with decreasing feed particle size and increasing ball size for most of the tested conditions. A selection function, αT, was formulated on the basis of the ball size for both Penouta mine samples. Finally, it was found that there does exist a direct relationship amongst Sn, Ta and Nb content, as metals of interest, in the milling product, the specific rate of breakage Si and the operational–mineralogical variables of ball size, mill speed and feed particle size.
A New 3D Cultured Liver Chip and Real-Time Monitoring System Based on Microfluidic Technology
Authors: Zhang Yao , Yang Ning , Xie Liangliang , Shu Fangyu , Shi Qian , Shaheen Naila
Published: December 2020

In vitro models of the liver have a good simulation of the micro-liquid environment inside the human liver and the communication between cell tissues, which provides an important research tool for drug research and liver disease treatment. In this paper, we designed a 3D liver chip and real-time monitoring system based on microfluidic technology. The in vitro model of the liver on the chip was established by the three-dimensional microfluidic chip pipeline and the corresponding microwell array. Meanwhile, the culture medium is continuously injected on the chip, and the electrochemical impedance spectroscopy and near-infrared spectroscopy of the liver chip are recorded and analyzed from day one to day five. When the 3D cultured liver chip in vitro model reached a certain period and stabilized, paracetamol with varying gradients of concentration was applied to the cultured cells for drug resistance testing. The experimental results show that the liver chip and its monitoring system designed in this paper can maintain 100% cell viability of hepatocytes in vitro for a long time. Furthermore, it can meet the requirements of measurement technologies such as electrical impedance measurement and near-infrared spectroscopy in real-time, providing a stable culture platform for the further study of organ chips.
Multiphysics Simulator for the IPMC Actuator: Mathematical Model, Finite Difference Scheme, Fast Numerical Algorithm, and Verification
Authors: Broyko Anton P. , Khmelnitskiy Ivan K. , Ryndin Eugeny A. , Korlyakov Andrey V. , Alekseyev Nikolay I. , Aivazyan Vagarshak M.
Published: December 2020

The article is devoted to the development and creation of a multiphysics simulator that can, on the one hand, simulate the most significant physical processes in the IPMC actuator, and on the other hand, unlike commercial products such as COMSOL, can use computing resources economically. The developed mathematical model is an adjoint differential equation describing the transport of charged particles and water molecules in the ion-exchange membrane, the electrostatic field inside, and the mechanical deformation of the actuator. The distribution of the electrostatic potential in the interelectrode space is located by means of the solution of the Poisson equation with the Dirichlet boundary conditions, where the charge density is a function of the concentration of cations inside the membrane. The cation distribution was obtained by means of the solution of the equation system, in which the fluxes of ions and water molecules are described by the modified Nernst-Planck equations with boundary conditions of the third kind (the Robin problem). The cantilever beam forced oscillation equation in the presence of resistance (allowing for dissipative processes) with assumptions of elasticity theory was used to describe the actuator motion. A combination of the following computational methods was used as a numerical algorithm for the solution: the Poisson equation was solved by a direct method, the modified Nernst-Planck equations were solved by the Newton-Raphson method, and the mechanical oscillation equation was solved using an explicit scheme. For this model, a difference scheme has been created and an algorithm has been described, which can be implemented in any programming language and allows for fast computational experiments. On the basis of the created algorithm and with the help of the obtained experimental data, a program has been created and the verification of the difference scheme and the algorithm has been performed. Model parameters have been determined, and recommendations on the ranges of applicability of the algorithm and the program have been given.
Biochar-Based Graphitic Carbon Nitride Adorned with Ionic Liquid Containing Acidic Polymer: A Versatile, Non-Metallic Catalyst for Acid Catalyzed Reaction
Authors: Sadjadi Samahe , Koohestani Fatemeh , Heravi Majid
Published: December 2020

A novel biochar-based graphitic carbon nitride was prepared through calcination of Zinnia grandiflora petals and urea. To provide acidic and ionic-liquid functionalities on the prepared carbon, the resultant biochar-based graphitic carbon nitride was vinyl functionalized and polymerized with 2-acrylamido-2-methyl-1-propanesulfonic acid, acrylic acid and the as-prepared 1-vinyl-3-butylimidazolium chloride. The final catalytic system that benefits from both acidic (–COOH and –SO3H) and ionic-liquid functionalities was applied as a versatile, metal-free catalyst for promoting some model acid catalyzed reactions such as Knoevenagel condensation and Biginelli reaction in aqueous media under a very mild reaction condition. The results confirmed high activity of the catalyst. Broad substrate scope and recyclability and stability of the catalyst were other merits of the developed protocols. Comparative experiments also indicated that both acidic and ionic-liquid functionalities on the catalyst participated in the catalysis.
Toxicological Screening of Four Bioactive Citroflavonoids: In Vitro, In Vivo, and In Silico Approaches
Authors: Ortiz-Andrade Rolffy , Araujo-León Jesús Alfredo , Sánchez-Recillas Amanda , Navarrete-Vazquez Gabriel , González-Sánchez Avel Adolfo , Hidalgo-Figueroa Sergio , Alonso-Castro Ángel Josabad , Aranda-González Irma , Hernández-Núñez Emanuel , Coral-Martínez Tania Isolina , Sánchez-Salgado Juan Carlos , Yáñez-Pérez Victor , Lucio-Garcia M. A.
Published: December 2020

Many studies describe different pharmacological effects of flavonoids on experimental animals and humans. Nevertheless, few ones are confirming the safety of these compounds for therapeutic purposes. This study aimed to investigate the preclinical safety of naringenin, naringin, hesperidin, and quercetin by in vivo, in vitro, and in silico approaches. For this, an MTT-based cytotoxicity assay in VERO and MDCK cell lines was performed. In addition, acute toxicity was evaluated on Wistar rats by OECD Guidelines for the Testing of Chemicals (Test No. 423: Acute Oral Toxicity-Class Method). Furthermore, we used the ACD/Tox Suite to predict toxicological parameters such as hERG channel blockade, CYP450 inhibition, and acute toxicity in animals. The results showed that quercetin was slightly more cytotoxic on cell lines (IC50 of 219.44 ± 7.22 mM and 465.41 ± 7.44 mM, respectively) than the other citroflavonoids. All flavonoids exhibited an LD50 value > 2000 mg/kg, which classifies them as low-risk substances as OECD guidelines established. Similarly, predicted LD50 was LD50 > 300 to 2000 mg/kg for all flavonoids as acute toxicity assay estimated. Data suggests that all these flavonoids did not show significant toxicological effects, and they were classified as low-risk, useful substances for drug development.
Chitin and Chitosan Derivatives as Biomaterial Resources for Biological and Biomedical Applications
Authors: Satitsri Saravut , Muanprasat Chatchai
Published: December 2020

Chitin is a long-chain polymer of N-acetyl-glucosamine, which is regularly found in the exoskeleton of arthropods including insects, shellfish and the cell wall of fungi. It has been known that chitin can be used for biological and biomedical applications, especially as a biomaterial for tissue repairing, encapsulating drug for drug delivery. However, chitin has been postulated as an inducer of proinflammatory cytokines and certain diseases including asthma. Likewise, chitosan, a long-chain polymer of N-acetyl-glucosamine and d-glucosamine derived from chitin deacetylation, and chitosan oligosaccharide, a short chain polymer, have been known for their potential therapeutic effects, including anti-inflammatory, antioxidant, antidiarrheal, and anti-Alzheimer effects. This review summarizes potential utilization and limitation of chitin, chitosan and chitosan oligosaccharide in a variety of diseases. Furthermore, future direction of research and development of chitin, chitosan, and chitosan oligosaccharide for biomedical applications is discussed.
How to Separate Kinase Inhibition from Undesired Monoamine Oxidase A Inhibition—The Development of the DYRK1A Inhibitor AnnH75 from the Alkaloid Harmine
Authors: Wurzlbauer Anne , Rüben Katharina , Gürdal Ece , Chaikuad Apirat , Knapp Stefan , Sippl Wolfgang , Becker Walter , Bracher Franz
Published: December 2020

The β-carboline alkaloid harmine is a potent DYRK1A inhibitor, but suffers from undesired potent inhibition of MAO-A, which strongly limits its application. We synthesized more than 60 analogues of harmine, either by direct modification of the alkaloid or by de novo synthesis of β-carboline and related scaffolds aimed at learning about structure–activity relationships for inhibition of both DYRK1A and MAO-A, with the ultimate goal of separating desired DYRK1A inhibition from undesired MAO-A inhibition. Based on evidence from published crystal structures of harmine bound to each of these enzymes, we performed systematic structure modifications of harmine yielding DYRK1A-selective inhibitors characterized by small polar substituents at N-9 (which preserve DYRK1A inhibition and eliminate MAO-A inhibition) and beneficial residues at C-1 (methyl or chlorine). The top compound AnnH75 remains a potent DYRK1A inhibitor, and it is devoid of MAO-A inhibition. Its binding mode to DYRK1A was elucidated by crystal structure analysis, and docking experiments provided additional insights for this attractive series of DYRK1A and MAO-A inhibitors.
Electrohydrodynamic Processing of Potato Protein into Particles and Fibers
Authors: Mendes Ana C. , Saldarini Elena , Chronakis Ioannis S.
Published: December 2020

Potato protein particles and fibers were produced using electrohydrodynamic processing (electrospray and electrospinning). The effect of different solvents and protein concentration on the morphology of the potato protein particles and fibers was investigated. Electrosprayed particles with average diameters ranging from 0.3 to 1.4 µm could be obtained using water and mixtures of water: ethanol (9:1) and water:glycerol (9:1). Electrosprayed particles were also obtained using the solvent hexafluoro-2-propanol (HFIP) at a protein concentration of 5% wt/v. For protein concentrations above 10% wt/v, using HFIP, electrospun fibers were produced. The release of vitamin B12, as a model bioactive compound, from potato protein electrospun fibers, was also investigated, demonstrating their potential to be utilized as encapsulation and delivery systems.
Nonvolatile, Reconfigurable and Narrowband Mid-Infrared Filter Based on Surface Lattice Resonance in Phase-Change Ge2Sb2Te5
Authors: Shi Xingzhe , Chen Changshui , Liu Songhao , Li Guangyuan
Published: December 2020

We propose a nonvolatile, reconfigurable, and narrowband mid-infrared bandpass filter based on surface lattice resonance in phase-change material Ge2Sb2Te5. The proposed filter is composed of a two-dimensional gold nanorod array embedded in a thick Ge2Sb2Te5 film. Results show that when Ge2Sb2Te5 transits from the amorphous state to the crystalline state, the narrowband reflection spectrum of the proposed filter is tuned from 3.197 μm to 4.795 μm, covering the majority of the mid-infrared regime, the peak reflectance decreases from 72.6% to 25.8%, and the corresponding quality factor decreases from 19.6 to 10.3. We show that the spectral tuning range can be adjusted by varying the incidence angle or the lattice period. By properly designing the gold nanorod sizes, we also show that the quality factor can be greatly increased to 70 at the cost of relatively smaller peak reflection efficiencies, and that the peak reflection efficiency can be further increased to 80% at the cost of relatively smaller quality factors. We expect that this work will advance the engineering of Ge2Sb2Te5-based nonvalatile tunable surface lattice resonances and will promote their applications especially in reconfigurable narrowband filters.
An Ultrahigh Sensitive Paper-Based Pressure Sensor with Intelligent Thermotherapy for Skin-Integrated Electronics
Authors: Gao Lin , Yu Junsheng , Li Ying , Wang Peiwen , Shu Jun , Deng Xiaoyan , Li Lu
Published: December 2020

Porous microstructure pressure sensors that are highly sensitive, reliable, low-cost, and environment-friendly have aroused wide attention in intelligent biomedical diagnostics, human–machine interactions, and soft robots. Here, an all-tissue-based piezoresistive pressure sensor with ultrahigh sensitivity and reliability based on the bottom interdigitated tissue electrode and the top bridge of a microporous tissue/carbon nanotube composite was proposed. Such pressure sensors exhibited ultrahigh sensitivity (≈1911.4 kPa−1), fast response time (<5 ms), low fatigue of over 2000 loading/unloading cycles, and robust environmental degradability. These enabled sensors can not only monitor the critical physiological signals of the human body but also realize electrothermal conversion at a specific voltage, which enhances the possibility of creating wearable thermotherapy electronics for protecting against rheumatoid arthritis and cervical spondylosis. Furthermore, the sensor successfully transmitted wireless signals to smartphones via Bluetooth, indicating its potential as reliable skin-integrated electronics. This work provides a highly feasible strategy for promoting high-performance wearable thermotherapy electronics for the next-generation artificial skin.
Improvement of Hypertriglyceridemia by Roasted Nelumbinis folium in High Fat/High Cholesterol Diet Rat Model
Authors: Kim Hye Yoom , Hong Mi Hyeon , Kim Kwan Woo , Yoon Jung Joo , Lee Jung Eun , Kang Dae Gill , Lee Ho Sub
Published: December 2020

Hypertriglyceridemia is a condition characterized by high triglyceride levels and is a major risk factor for the development of cardiovascular diseases. The present study was designed to investigate the inhibitory effect of roasted Nelumbinis folium (RN), which is a medicinal substance produced by heating lotus leaves, on lipid metabolism in high fat/cholesterol (HFC) diet-induced hypertriglyceridemia. Except for those in the control group, Sprague–Dawley rats were fed an HFC diet for four weeks to induce hypertriglyceridemia. During the next nine weeks, the control, regular diet; HFC, HFC diet, FLU, fluvastatin (3 mg/kg/day); RNL, RN (100 mg/kg/day); RNH, RN (200 mg/kg/day) were orally administered together with the diet, and the experiments were conducted for a total of 13 weeks. The weight of the epididymal adipose tissue, liver, and heart of rats in the HFC diet group significantly increased compared to those in the control group but improved in the RN-treated group. It was also confirmed that vascular function, which is damaged by an HFC diet, was improved after RN treatment. The levels of insulin, glucose, triglycerides, total cholesterol, and low-density lipoprotein increased in the HFC diet group compared to those in the control group, while the administration of RN attenuated these parameters. In addition, the administration of RN significantly reduced the gene expression of both LXR and SREBP-1, which indicated the inhibitory effect of the biosynthesis of triglycerides caused by RN. The results indicated that RN administration resulted in an improvement in the overall lipid metabolism and a decrease in the concentration of triglycerides in the HFC diet-induced rat model of hypertriglyceridemia. Therefore, our findings suggest that the RN can be a candidate material to provide a new direction for treating hypertriglyceridemia.
Nutritional Approaches for the Management of Nonalcoholic Fatty Liver Disease: An Evidence-Based Review
Authors: Parra-Vargas Marcela , Rodriguez-Echevarria Roberto , Jimenez-Chillaron Josep C.
Published: December 2020

Nonalcoholic fatty liver disease (NAFLD) is on the rise worldwide representing a public health issue. Its coexistence with obesity and other metabolic alterations is highly frequent. Therefore, current therapy interventions for NAFLD are mainly focused on progressive weight loss through modulation of overall calorie intake with or without specific macronutrient adjustments. Furthermore, other relevant nutritional interventions are built on food selection and time-restricted eating. Since every strategy might bring different results, choosing the optimal diet therapy for a patient is a complicated task, because NAFLD is a multifactorial complex disease. Importantly, some factors need to be considered, such as nutrition-based evidence in terms of hepatic morphophysiological improvements as well as adherence of the patient to the meal plan and adaptability in their cultural context. Thus, the purpose of this review is to explore and compare the subtleties and nuances of the most relevant clinical practice guidelines and the nutritional approaches for the management of NAFLD with a special attention to tangible outcomes and long-term adherence.
Acrylamide–Hemoglobin Adduct Levels in a Japanese Population and Comparison with Acrylamide Exposure Assessed by the Duplicated Method or a Food Frequency Questionnaire
Authors: Yamamoto Junpei , Ishihara Junko , Matsui Yasuto , Matsuda Tomonari , Kotemori Ayaka , Zheng Yazhi , Nakajima Daisuke , Terui Miho , Shinohara Akiko , Adachi Shuichi , Kawahara Junko , Sobue Tomotaka
Published: December 2020

The levels of hemoglobin adducts of acrylamide (AA–Hb), a biomarker of acrylamide exposure, have not been reported for Japanese subjects. Herein, we determined the AA–Hb levels in a Japanese population and compared them with the estimated dietary intake from the duplicate diet method (DM) and a food frequency questionnaire (FFQ). One-day DM samples, FFQ, and blood samples were collected from 89 participants and analyzed for acrylamide. AA–Hb was analyzed using liquid chromatography tandem mass spectrometry and the N-alkyl Edman method. Participants were divided into tertiles of estimated acrylamide intake and geometric means (GMs) of AA–Hb adjusted for sex and smoking status. A stratified analysis according to smoking status was also performed. The average AA–Hb levels for all participants, never, past, and current smokers were 46, 38, 65, and 86 pmol/g Hb, respectively. GMs of AA–Hb levels in all participants were significantly associated with tertiles of estimated acrylamide intake from DM (p for trend = 0.02) and FFQ (p for trend = 0.04), although no association with smokers was observed. AA–Hb levels reflected smoking status, which were similar to values reported in Western populations, and they were associated with estimated dietary intake of acrylamide when adjusted for sex and smoking status.
Enhancing the Poor Flow and Tableting Problems of High Drug-Loading Formulation of Canagliflozin Using Continuous Green Granulation Process and Design-of-Experiment Approach
Authors: Almutairy Bjad K. , Khafagy El-Sayed , Alalaiwe Ahmed , Aldawsari Mohammed F. , Alshahrani Saad M. , Alsulays Bader B. , Alshetaili Abdullah S. , Alshehri Sultan M. , Fayed Mohamed H.
Published: December 2020

Maximization of drug-loading can significantly reduce the size of dosage form and consequently decrease the cost of manufacture. In this research, two challenges were addressed: poor flow and tableting problems of high-drug loading (>70%) formulation of canagliflozin (CNG), by adopting the moisture-activated dry granulation (MADG) process. In this method, heating and drying steps were omitted so, called green granulation process. A 32 full-factorial design was performed for optimization of key process variables, namely the granulation fluid level (X1) and the wet massing time (X2). Granulation of CNG was carried out in the presence of polyvinylpyrrolidone, and the prepared granules were compressed into tablets. Regression analysis demonstrated the significant (p ≤ 0.05) effect of X1 and X2 on properties of granules and corresponding tablets, with pronounced impact of X1. Additionally, marked improvement of granules’ properties and tableting of CNG were observed. Furthermore, the optimized process conditions that produced good flow properties of granules and acceptable tablets were high level of granulation fluid (3.41% w/w) and short wet massing time (1.0 min). Finally, the MADG process gives the opportunity to ameliorate the poor flow and tableting problems of CNG with lower amounts of excipients, which are important for successful development of uniform dosage unit.
In Vivo Bactericidal Efficacy of GWH1 Antimicrobial Peptide Displayed on Protein Nanoparticles, a Potential Alternative to Antibiotics
Authors: Carratalá Jose V. , Brouillette Eric , Serna Naroa , Sánchez-Chardi Alejandro , Sánchez Julieta M. , Villaverde Antonio , Arís Anna , Garcia-Fruitós Elena , Ferrer-Miralles Neus , Malouin François
Published: December 2020

Oligomerization of antimicrobial peptides into nanosized supramolecular complexes produced in biological systems (inclusion bodies and self-assembling nanoparticles) seems an appealing alternative to conventional antibiotics. In this work, the antimicrobial peptide, GWH1, was N-terminally fused to two different scaffold proteins, namely, GFP and IFN-γ for its bacterial production in the form of such recombinant protein complexes. Protein self-assembling as regular soluble protein nanoparticles was achieved in the case of GWH1-GFP, while oligomerization into bacterial inclusion bodies was reached in both constructions. Among all these types of therapeutic proteins, protein nanoparticles of GWH1-GFP showed the highest bactericidal effect in an in vitro assay against Escherichia coli, whereas non-oligomerized GWH1-GFP and GWH1-IFN-γ only displayed a moderate bactericidal activity. These results indicate that the biological activity of GWH1 is specifically enhanced in the form of regular multi-display configurations. Those in vitro observations were fully validated against a bacterial infection using a mouse mastitis model, in which the GWH1-GFP soluble nanoparticles were able to effectively reduce bacterial loads.
Correction: López-Yerena, A., et al. “Absorption and Intestinal Metabolic Profile of Oleocanthal in Rats” Pharmaceutics 2020, 12, 134
Authors: López-Yerena Anallely , Vallverdú-Queralt Anna , Mols Raf , Augustijns Patrick , Lamuela-Raventós Rosa M. , Escribano-Ferrer Elvira
Published: December 2020

The authors would like to make the following corrections to this paper [...]
Performance Analysis and Enhancement of Free Space Optical Links for Developing State-of-the-Art Smart City Framework
Authors: Chauhan Sonali , Miglani Rajan , Kansal Lavish , Gaba Gurjot Singh , Masud Mehedi
Published: December 2020

In this paper, we have investigated and reported the performance of free-space optical (FSO) links operating in adverse atmospheric conditions. Since FSO links share operational similarity with fiber communication; hence, we believe that a cost-effective FSO framework can play a significant role in the transparent integration of high-speed network access backbones with the end-users. Different modulation formats, complemented with spatial diversity techniques, are discussed in this paper to strategize performance optimization of FSO links. Using bit error rate (BER) and signal-to-noise ratio (SNR) as performance metrics, it was found that binary phase-shift keying (BPSK) qualifies as the best technique modulation technique delivering SNR gain of 10 dB over on–off keying (OOK) operating link under similar channel conditions. Further performance optimization was achieved using space diversity reception wherein SNR witnessed a gain of 3 dB gain over the single-channel FSO link. In terms of application, the proposed model can help in developing a citizen-centric smart city ecosystem that can support seamless communication between heterogeneous smart devices.
High Efficiency and Low Migration Hyperbranched Silicone Contain Macrophotoinitiators for UV-Cured Transparent Coatings
Authors: Fan Yunxin , Song Yan , He Na , Cheng Fei , Jiao Xiaojiao , Lai Guoqiao , Hua Xilin , Yang Xiongfa
Published: December 2020

A kind of hyperbranched silicone containing macrophotoinitiators (HBSMIs) were synthesized from 2-hydroxy-2-methyl-1-phenyl propanone (HMPP) and the UV-curing behaviors of HBSMIs were investigated in UV-cured transparent polyurethane-acrylate (PUA) coatings. HBSMIs show higher UV-initiating efficiency than HMPP. The migration of HBSMIs from the UV-cured coatings can be as low as 1.7–6.0 wt%, which is obviously lower than the migration of HMPP. There is a remarkable improvement of the tensile strength of the UV-cured materials initiated by HBSMI in comparison to that of the materials prepared with the same PUA initiated by HMPP. Especially for the UV-cured materials prepared from PUA with 20 wt% 1,1,1-tris(hydroxymethyl)propane (TMP), the tensile strength and the strain at break increased from 6.81 MPa to 12.14 MPa and from 43.0% to 71.9%, respectively. The fraction of improvement for the tensile strength and the strain at break is as high as 78.9% and 67.2%, respectively. The coatings prepared with HBSMI also have better UV resistance ability than those coatings prepared with HMPP because they turn slightly yellow when they are aged by UV for about 15 min while the coating prepared with 4 wt% of HMPP will turn yellow only aged by UV for 2 min. These results suggest that preparation hyperbranched silicone containing macrophotoinitiators will be one of the good strategies to improve the curing efficiency of the UV-curing system, reduce the migration of UV initiator from cured material, improve the mechanical and UV resistance performance of UV-cured materials.
How Do Indirect Effects of Contaminants Inform Ecotoxicology? A Review
Authors: Fleeger John W.
Published: December 2020

Indirect effects in ecotoxicology are defined as chemical- or pollutant-induced alterations in the density or behavior of sensitive species that have cascading effects on tolerant species in natural systems. As a result, species interaction networks (e.g., interactions associated with predation or competition) may be altered in such a way as to bring about large changes in populations and/or communities that may further cascade to disrupt ecosystem function and services. Field studies and experimental outcomes as well as models indicate that indirect effects are most likely to occur in communities in which the strength of interactions and the sensitivity to contaminants differ markedly among species, and that indirect effects will vary over space and time as species composition, trophic structure, and environmental factors vary. However, knowledge of indirect effects is essential to improve understanding of the potential for chemical harm in natural systems. For example, indirect effects may confound laboratory-based ecological risk assessment by enhancing, masking, or spuriously indicating the direct effect of chemical contaminants. Progress to better anticipate and interpret the significance of indirect effects will be made as monitoring programs and long-term ecological research are conducted that facilitate critical experimental field and mesocosm investigations, and as chemical transport and fate models, individual-based direct effects models, and ecosystem/food web models continue to be improved and become better integrated.
Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices
Authors: Sun Shaobo , Zhang Yonggen , Song Zhaoliang , Chen Baozhang , Zhang Yangjian , Yuan Wenping , Chen Chu , Chen Wei , Ran Xiangbin , Wang Yidong
Published: December 2020

Coastal wetlands provide essential ecosystem services and are closely related to human welfare. However, they can experience substantial degradation, especially in regions in which there is intense human activity. To control these increasingly severe problems and to develop corresponding management policies in coastal wetlands, it is critical to accurately map coastal wetlands. Although remote sensing is the most efficient way to monitor coastal wetlands at a regional scale, it traditionally involves a large amount of work, high cost, and low spatial resolution when mapping coastal wetlands at a large scale. In this study, we developed a workflow for rapidly mapping coastal wetlands at a 10 m spatial resolution, based on the recently emergent Google Earth Engine platform, using a machine learning algorithm, open-access Synthetic Aperture Radar (SAR) and optical images from the Sentinel satellites, and two terrain indices. We then generated a coastal wetland map of the Bohai Rim (BRCW10) based on the workflow. It has a producer accuracy of 82.7%, according to validation using 150 wetland samples. The BRCW10 data reflected finer information when compared to wetland maps derived from two sets of global high-spatial-resolution land cover data, due to the fusion of multiple data sources. The study highlights the benefits of simultaneously merging SAR and optical remote sensing images when mapping coastal wetlands.
Adaptive Distance-Weighted Voronoi Tessellation for Remote Sensing Image Segmentation
Authors: Li Xiaoli , Chen Jinsong , Zhao Longlong , Guo Shanxin , Sun Luyi , Zhao Xuemei
Published: December 2020

The spatial fragmentation of high-resolution remote sensing images makes the segmentation algorithm put forward a strong demand for noise immunity. However, the stronger the noise immunity, the more serious the loss of detailed information, which easily leads to the neglect of effective characteristics. In view of the difficulty of balancing the noise immunity and effective characteristic retention, an adaptive distance-weighted Voronoi tessellation technology is proposed for remote sensing image segmentation. The distance between pixels and seed points in Voronoi tessellation is established by the adaptive weighting of spatial distance and spectral distance. The weight coefficient used to control the influence intensity of spatial distance is defined by a monotone decreasing function. Following the fuzzy clustering framework, a fuzzy segmentation model with Kullback–Leibler (KL) entropy regularization is established by using multivariate Gaussian distribution to describe the spectral characteristics and Markov Random Field (MRF) to consider the neighborhood effect of sub-regions. Finally, a series of parameter optimization schemes are designed according to parameter characteristics to obtain the optimal segmentation results. The proposed algorithm is validated on many multispectral remote sensing images with five comparing algorithms by qualitative and quantitative analysis. A large number of experiments show that the proposed algorithm can overcome the complex noise as well as better ensure effective characteristics.
Bi-Temporal Analysis of Spatial Changes of Boreal Forest Cover and Species in Siberia for the Years 1985 and 2015
Authors: Tian Lei , Fu Wenxue
Published: December 2020

Boreal forest is a sensitive indicator of the influence of climate change. It can quantify the level and spatial divergence of forest change for forest resources and carbon cycle research. This study selected a typical boreal forest affected by few human activities as a research area, in Siberia, with a latitude span of 51°N–69°N. A total of 150 Landsat images of this area acquired in 1985 and 2015 were collected. A hierarchical classification approach was first established to retrieve the information of forest cover and species. The forested and nonforested lands were discriminated by the decision tree method and, furthermore, the forested land was classified to broad-leaved and coniferous forests by a random forest algorithm. The overall accuracy was 90.37%, which indicates the validity of the approach. Finally, the quantitative information of the forest cover and species changes in each latitude zone of every 2° was analyzed. The results show that the overall boreal forest cover increased by 5.11% over the past three decades, with broad-leaved forest increasing by 3.54% and coniferous forest increasing by 1.57%. In addition, boreal forest increased in every latitude zone, and the spatial divergence of the changes of the boreal forest cover and species in different latitude zones were significant. Finally, broad-leaved forest increased more rapidly than coniferous forest, and the greatest increase, of up to 5.77%, occurred in the zone of 55°N–57°N.
Integrating Remote Sensing and Landscape Characteristics to Estimate Soil Salinity Using Machine Learning Methods: A Case Study from Southern Xinjiang, China
Authors: Wang Nan , Xue Jie , Peng Jie , Biswas Asim , He Yong , Shi Zhou
Published: December 2020

Soil salinization, one of the most severe global land degradation problems, leads to the loss of arable land and declines in crop yields. Monitoring the distribution of salinized soil and degree of salinization is critical for management, remediation, and utilization of salinized soil; however, there is a lack of thorough assessment of various data sources including remote sensing and landscape characteristics for estimating soil salinity in arid and semi-arid areas. The overall goal of this study was to develop a framework for estimating soil salinity in diverse landscapes by fusing information from satellite images, landscape characteristics, and appropriate machine learning models. To explore the spatial distribution of soil salinity in southern Xinjiang, China, as a case study, we obtained 151 soil samples in a field campaign, which were analyzed in laboratory for soil electrical conductivity. A total of 35 indices including remote sensing classifiers (11), terrain attributes (3), vegetation spectral indices (8), and salinity spectral indices (13) were calculated or derived and correlated with soil salinity. Nine were used to model and estimate soil salinity using four predictive modelling approaches: partial least squares regression (PLSR), convolutional neural network (CNN), support vector machine (SVM) learning, and random forest (RF). Testing datasets were divided into vegetation-covered and bare soil samples and were used for accuracy assessment. The RF model was the best regression model in this study, with R2 = 0.75, and was most effective in revealing the spatial characteristics of salt distribution. Importance analysis and path modeling of independent variables indicated that environmental factors and soil salinity indices including digital elevation model (DEM), B10, and green atmospherically resistant vegetation index (GARI) showed the strongest contribution in soil salinity estimation. This showed a great promise in the measurement and monitoring of soil salinity in arid and semi-arid areas from the integration of remote sensing, landscape characteristics, and using machine learning model.
Improvement and Impacts of Forest Canopy Parameters on Noah-MP Land Surface Model from UAV-Based Photogrammetry
Authors: Chang Ming , Zhu Shengjie , Cao Jiachen , Chen Bingyin , Zhang Qi , Chen Weihua , Jia Shiguo , Krishnan Padmaja , Wang Xuemei
Published: December 2020

Taking a typical forest’s underlying surface as our research area, in this study, we employed unmanned aerial vehicle (UAV) photogrammetry to explore more accurate canopy parameters including the tree height and canopy radius, which were used to improve the Noah-MP land surface model, which was conducted in the Dinghushan Forest Ecosystem Research Station (CN-Din). While the canopy radius was fitted as a Burr distribution, the canopy height of the CN-Din forest followed a Weibull distribution. Then, the canopy parameter distribution was obtained, and we improved the look-up table values of the Noah-MP land surface model. It was found that the influence on the simulation of the energy fluxes could not be negligible, and the main influence of these canopy parameters was on the latent heat flux, which could decrease up to −11% in the midday while increasing up to 15% in the nighttime. Additionally, this work indicated that the description of the canopy characteristics for the land surface model should be improved to accurately represent the heterogeneity of the underlying surface.
Comparison of Canopy Shape and Vegetation Indices of Citrus Trees Derived from UAV Multispectral Images for Characterization of Citrus Greening Disease
Authors: Chang Anjin , Yeom Junho , Jung Jinha , Landivar Juan
Published: December 2020

Citrus greening is a severe disease significantly affecting citrus production in the United States because the disease is not curable with currently available technologies. For this reason, monitoring citrus disease in orchards is critical to eradicate and replace infected trees before the spread of the disease. In this study, the canopy shape and vegetation indices of infected and healthy orange trees were compared to better understand their significant characteristics using unmanned aerial vehicle (UAV)-based multispectral images. Individual citrus trees were identified using thresholding and morphological filtering. The UAV-based phenotypes of each tree, such as tree height, crown diameter, and canopy volume, were calculated and evaluated with the corresponding ground measurements. The vegetation indices of infected and healthy trees were also compared to investigate their spectral differences. The results showed that correlation coefficients of tree height and crown diameter between the UAV-based and ground measurements were 0.7 and 0.8, respectively. The UAV-based canopy volume was also highly correlated with the ground measurements (R2 > 0.9). Four vegetation indices—normalized difference vegetation index (NDVI), normalized difference RedEdge index (NDRE), modified soil adjusted vegetation index (MSAVI), and chlorophyll index (CI)—were significantly higher in healthy trees than diseased trees. The RedEdge-related vegetation indices showed more capability for citrus disease monitoring. Additionally, the experimental results showed that the UAV-based flush ratio and canopy volume can be valuable indicators to differentiate trees with citrus greening disease.
Regional Level Data Server for Fire Hazard Evaluation and Fuel Treatments Planning
Authors: Krsnik Goran , Busquets Olivé Eduard , Piqué Nicolau Míriam , Larrañaga Asier , Cardil Adrián , García-Gonzalo Jordi , González Olabarría José Ramón
Published: December 2020

Both fire risk assessment and management of wildfire prevention strategies require different sources of data to represent the complex geospatial interaction that exists between environmental variables in the most accurate way possible. In this sense, geospatial analysis tools and remote sensing data offer new opportunities for estimating fire risk and optimizing wildfire prevention planning. Herein, we presented a conceptual design of a server that contained most variables required for predicting fire behavior at a regional level. For that purpose, an innovative and elaborated fuel modelling process and parameterization of all needed environmental and climatic variables were implemented in order to enable to more precisely define fuel characteristics and potential fire behaviors under different meteorological scenarios. The server, open to be used by scientists and technicians, is expected to be the steppingstone for an integrated tool to support decision-making regarding prevention and management of forest fires in Catalonia.
Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations
Authors: She Lu , Zhang Hankui K. , Li Zhengqiang , de Leeuw Gerrit , Huang Bo
Published: December 2020

Spectral aerosol optical depth (AOD) estimation from satellite-measured top of atmosphere (TOA) reflectances is challenging because of the complicated TOA-AOD relationship and a nexus of land surface and atmospheric state variations. This task is usually undertaken using a physical model to provide a first estimate of the TOA reflectances which are then optimized by comparison with the satellite data. Recently developed deep neural network (DNN) models provide a powerful tool to represent the complicated relationship statistically. This study presents a methodology based on DNN to estimate AOD using Himawari-8 Advanced Himawari Imager (AHI) TOA observations. A year (2017) of AHI TOA observations over the Himawari-8 full disk collocated in space and time with Aerosol Robotic Network (AERONET) AOD data were used to derive a total of 14,154 training and validation samples. The TOA reflectance in all six AHI solar bands, three TOA reflectance ratios derived based on the dark-target assumptions, sun-sensor geometry, and auxiliary data are used as predictors to estimate AOD at 500 nm. The DNN AOD is validated by separating training and validation samples using random k-fold cross-validation and using AERONET site-specific leave-one-station-out validation, and is compared with a random forest regression estimator and Japan Meteorological Agency (JMA) AOD. The DNN AOD shows high accuracy: (1) RMSE = 0.094, R2 = 0.915 for k-fold cross-validation, and (2) RMSE = 0.172, R2 = 0.730 for leave-one-station-out validation. The k-fold cross-validation overestimates the DNN accuracy as the training and validation samples may come from the same AHI pixel location. The leave-one-station-out validation reflects the accuracy for large-area applications where there are no training samples for the pixel location to be estimated. The DNN AOD has better accuracy than the random forest AOD and JMA AOD. In addition, the contribution of the dark-target derived TOA ratio predictors is examined and confirmed, and the sensitivity to the DNN structure is discussed.
Surface Subsidence in Urbanized Coastal Areas: PSI Methods Based on Sentinel-1 for Ho Chi Minh City
Authors: Duffy C. Elizabeth , Braun Andreas , Hochschild Volker
Published: December 2020

In Ho Chi Minh City (HCMC), Vietnam, though at present flooding is merely a recurring nuisance, there is increasing concern that a combination of impending climate change and rapid urbanization will significantly exacerbate the situation. Given the significant measures taken in HCMC to reduce groundwater extraction and sea-level rise (SLR) inundation since the most recent subsidence studies, we aim to update and contribute to the subsidence information of HCMC with continuous temporal coverage from 2017 to 2019. In this study, we use Persistent Scatterer Interferometry (PSI) with Copernicus Sentinel-1 data and open source tools to determine current subsidence rates within the urban center of HCMC. Additionally, the scalability of this method and use of freely accessible data allows for continuous updating and monitoring of this high-vulnerability region. The observed average subsidence rates were 3.3 mm per year with a maximum local subsidence of 5.3 cm per year. These results largely align with findings of previous studies and reflect similar spatial distributed subsidence patterns. Inundation risk awareness is enhanced by not only continued improved subsidence analysis, but also incorporating latest advancements in Digital Elevation Model (DEM) accuracy. This study compares local differences between traditionally used AW3D30 DEM with the CoastalDEM. Our findings indicate that although we identify lower than previously accepted elevations in the urban core, that stabilization of subsidence is observed in this same region.
NDVI Dynamics and Its Response to Climate Change and Reforestation in Northern China
Authors: Lin Xingna , Niu Jianzhi , Berndtsson Ronny , Yu Xinxiao , Zhang Linus , Chen Xiongwen
Published: December 2020

Vegetation is an important component of the terrestrial ecosystem that plays an essential role in the exchange of water and energy in climate and biogeochemical cycles. This study investigated the spatiotemporal variation of normalized difference vegetation index (NDVI) in northern China using the GIMMS-MODIS NDVI during 1982–2018. We explored the dominant drivers of NDVI change using regression analyses. Results show that the regional average NDVI for northern China increased at a rate of 0.001 year−1. NDVI improved and degraded area corresponded to 36.1% and 9.7% of the total investigated area, respectively. Climate drivers were responsible for NDVI change in 46.2% of the study area, and the regional average NDVI trend in the region where the dominant drivers were temperature (T), precipitation (P), and the combination of precipitation and temperature (P&T), increased at a rate of 0.0028, 0.0027, and 0.0056 year−1, respectively. We conclude that P has positive dominant effects on NDVI in the subregion VIAiia, VIAiic, VIAiib, VIAib of temperate grassland region, and VIIBiia of temperate desert region in northern China. T has positive dominant effects on NDVI in the alpine vegetation region of Qinghai Tibet Plateau. NDVI is negatively dominated by T in the subregion VIIBiib, VIIBib, VIIAi, and VIIBi of temperate desert regions. Human activities affect NDVI directly by reforestation, especially in Shaanxi, Shanxi, and Hebei provinces.
The Characterization Pattern of Overburden Deformation with Distributed Optical Fiber Sensing: An Analogue Model Test and Extensional Analysis
Authors: Yuan Qiang , Chai Jing , Ren Yiwei , Liu Yongliang
Published: December 2020

The evolution of overburden deformation is crucial for safety and environmental efficiency and its monitoring is becoming a key scientific issue. The use of an optical fiber sensor (OFS) for mining engineering is now receiving praise by virtue of its distinct abilities of distribution, high accuracy, and anti-interference measurement. Nevertheless, the dynamic response of OFS monitoring on overburden deformation still needs to be characterized in detail. This paper analyzed the characterization pattern of overburden deformation based on distributed optical fiber sensing (DOFS) by means of an analogue model test. Then, we discuss the influence of rules of optical fiber embedding on a model test in a numerical simulation. The results show that the DOFS monitoring demonstrates the time-space evolution of overburden deformation and the development of three horizontal areas and three vertical zones. A standardization DOFS characterization model is proposed to expound the characterization mechanism of the overburden structure zoning process; the influence of optical fiber embedding on rock displacement in the model test is revealed, and it is found that the displacement error will increase sharply when the fiber diameter is larger than 2 mm. These findings could provide an effective solution for a monitoring method in intelligent mining from the perspective of a theoretical basis and technological system.