bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Study on the Variability of Plastic CTOD
Authors: André Prates Pedro , Eusébio Marques Armando , Frias Borges Micael , Madeira Branco Ricardo , Antunes Fernando Ventura
Published: March 2020

This paper presents a numerical study on the influence of material parameters and loading variability in the plastic crack tip opening displacement (CTOD) results. For this purpose, AA7050-T6 was selected as reference material and a middle-cracked tension specimen geometry was considered. The studied input parameters were the Young’s modulus, Poisson’s ratio, isotropic and kinematic hardening parameters and the maximum and minimum applied loads. The variability of the input parameters follows a Gaussian distribution. First, screening design-of-experiments were performed to identify the most influential parameters. Two types of screening designs were considered: one-factor-at-a-time and fractional factorial designs. Three analysis criteria were adopted, based on: main effect, index of influence and analysis of variance. Afterwards, metamodels were constructed to establish relationships between the most influential parameters and the plastic crack tip opening displacement (CTOD) range, based on two types of designs: Face-Centered Central Composite Design and Box-Behnken design. Finally, the metamodels were validated, enabling the expeditious evaluation of the variability in the plastic CTOD range; in addition, the variability in the fatigue crack growth rate was also evaluated.
Correction: Speranza, V. et al. Hierarchical Structure of iPP During Injection Molding Process with Fast Mold Temperature Evolution. Materials 2019, 12, 424
Authors: Speranza Vito , Liparoti Sara , Pantani Roberto , Titomanlio Giuseppe
Published: March 2020

The correction reported in the following has to be applied to the paper [...]
An Investigation into the Dynamic Recrystallization (DRX) Behavior and Processing Map of 33Cr23Ni8Mn3N Based on an Artificial Neural Network (ANN)
Authors: Cai Zhongman , Ji Hongchao , Pei Weichi , Tang Xuefeng , Xin Long , Lu Yonghao , Li Wangda
Published: March 2020

Based on an 33Cr23Ni8Mn3N thermal simulation experiment, the application of an artificial neural network (ANN) in thermomechanical processing was studied. Based on the experimental data, a microstructure evolution model and constitutive equation of 33Cr23Ni8Mn3N heat-resistant steel were established. Stress, dynamic recrystallization (DRX) fraction, and DRX grain size were predicted. These models were evaluated by a variety of statistical indicators to determine that these models would work well if applied in predicting microstructure evolution and that they have high precision. Then, based on the weight of the ANN model, the sensitivity of the input parameters was analyzed to achieve an optimized ANN model. Based on the most widely used sensitivity analysis (SA) method (the Garson method), the input parameters were analyzed. The results show that the most important factor for the microstructure of 33Cr23Ni8Mn3N is the strain rate ( ε ˙ ). For the control of the microstructure, the control of the ε ˙ is preferred. ANN was applied to the development of processing map. The feasibility of the ANN processing map on austenitic heat-resistant steel was verified by experiments. The results show that the ANN processing map is basically consistent with processing map based on experimental data. The trained ANN model was implanted into finite element simulation software and tested. The test results show that the ANN model can accurately expand the data volume to achieve high precision simulation results.
Advances in Atomic Layer Deposition (ALD) Nanolaminate Synthesis of Thermoelectric Films in Porous Templates for Improved Seebeck Coefficient
Authors: Chen Xin , Baumgart Helmut
Published: March 2020

Thermoelectrics is a green renewable energy technology which can significantly contribute to power generation due to its potential in generating electricity out of waste heat. The main challenge for the development of thermoelectrics is its low conversion efficiency. One key strategy to improve conversion efficiency is reducing the thermal conductivity of thermoelectric materials. In this paper, the state-of-the-art progresses made in improving thermoelectric materials are reviewed and discussed, focusing on phononic engineering via applying porous templates and ALD deposited nanolaminates structure. The effect of nanolaminates structure and porous templates on Seebeck coefficient, electrical conductivity and thermal conductivity, and hence in figure of merit zT of different types of materials system, including PnCs, lead chalcogenide-based nanostructured films on planar and porous templates, ZnO-based superlattice, and hybrid organic-inorganic superlattices, will be reviewed and discussed.
Advances in Ultrasonic Welding of Thermoplastic Composites: A Review
Authors: Bhudolia Somen K. , Gohel Goram , Leong Kah Fai , Islam Aminul
Published: March 2020

The ultrasonic welding (UW) technique is an ultra-fast joining process, and it is used to join thermoplastic composite structures, and provides an excellent bonding strength. It is more cost-efficient as opposed to the conventional adhesive, mechanical and other joining methods. This review paper presents the detailed progress made by the scientific and research community to date in the direction of the UW of thermoplastic composites. The focus of this paper is to review the recent development of the ultrasonic welding technique for thermoplastic composites to thermoplastic composites, and to dissimilar materials. Different ultrasonic welding modes and their processing parameters, namely, weld time, weld pressure, amplitude, type of energy directors (EDs) affecting the welding quality and the advantages and disadvantages of UW over other bonding techniques, are summarized. The current state of the ultrasonic welding of thermoplastic composites and their future perspectives are also deliberated.
Effect of Surface Inhomogeneity of Ion-Exchange Membranes on the Mass Transfer Efficiency in Pulsed Electric Field Modes
Authors: Butylskii Dmitrii , Moroz Ilya , Tsygurina Kseniya , Mareev Semyon
Published: March 2020

Despite the growing interest in pulsed electric field modes in membrane separation processes, there are currently not many works devoted to studying the effect of the surface properties and composition of ion-exchange membranes on their efficiency in these modes. In this paper, we have shown the effect of increasing mass transfer using different kinds of ion-exchange membranes (heterogeneous and homogeneous with smooth, undulated, and rough surfaces) during electrodialysis in the pulsed electric field modes at underlimiting and overlimiting currents. It was found that the maximum increment in the average current is achieved when the average potential corresponds to the right-hand edge of the limiting current plateau of the voltammetric curve, i.e., at the maximum resistance of the system in the DC mode. For the first time, the development of electroconvective vortices was visualized in pulsed electric field modes and it was experimentally shown that even at relatively low frequencies, a non-uniform concentration field is preserved at the time of a pause, which stimulates the rapid development of electroconvection when pulses are switched on again. In the case of relatively high pulse frequencies, the electroconvective vortices formed during a pulse lapse do not completely decay during a pause; they only slightly decrease in size.
Carbon Impact Mitigation of the Iron Ore Direct Reduction Process through Computer-Aided Optimization and Design Changes
Authors: Béchara Rami , Hamadeh Hamzeh , Mirgaux Olivier , Patisson Fabrice
Published: March 2020

The steel industry is known to have one of the highest environmental impacts on the industrial sector, especially in terms of CO2 emissions. The so-called direct reduction route, which makes use of reformed natural gas along with top gas recycling to reduce iron oxide pellets with H2 and CO, is responsible for lower CO2 emissions than the classic blast furnace route and is currently under development. The present article focuses on the direct reduction process and discusses means to further decrease the CO2 emission rate. A set of 10 operating parameters were simultaneously changed according to computer-aided optimization. The results provide about 15% improvement over original emissions for comparable output values.
A Quantitative Assessment of Methane-Derived Carbon Cycling at the Cold Seeps in the Northwestern South China Sea
Authors: Feng Junxi , Li Niu , Luo Min , Liang Jinqiang , Yang Shengxiong , Wang Hongbin , Chen Duofu
Published: March 2020

Widespread cold seeps along continental margins are significant sources of dissolved carbon to the ocean water. However, little is known about the methane turnovers and possible impact of seepage on the bottom seawater at the cold seeps in the South China Sea (SCS). We present seafloor observation and porewater data of six push cores, one piston core and three boreholes as well as fifteen bottom-water samples collected from four cold seep areas in the northwestern SCS. The depths of the sulfate–methane transition zone (SMTZ) are generally shallow, ranging from ~7 to <0.5 mbsf (meters below seafloor). Reaction-transport modelling results show that methane dynamics were highly variable due to the transport and dissolution of ascending gas. Dissolved methane is predominantly consumed by anaerobic oxidation of methane (AOM) at the SMTZ and trapped by gas hydrate formation below it, with depth-integrated AOM rates ranging from 59.0 and 591 mmol m−2 yr−1. The δ13C and Δ14C values of bottom-water dissolved inorganic carbon (DIC) suggest discharge of 13C- and 14C-depleted fossil carbon to the bottom water at the cold seep areas. Based on a two-endmember estimate, cold seeps fluids likely contribute 16–26% of the bottom seawater DIC and may have an impact on the long-term deep-sea carbon cycle. Our results reveal the methane-related carbon inventories are highly heterogeneous in the cold seep systems, which are probably dependent on the distances of the sampling sites to the seepage center. To our knowledge, this is the first quantitative study on the contribution of cold seep fluids to the bottom-water carbon reservoir of the SCS, and might help to understand the dynamics and the environmental impact of hydrocarbon seep in the SCS.
White Magnetic Paper with Zero Remanence Based on Electrospun Cellulose Microfibers Doped with Iron Oxide Nanoparticles
Authors: Papaparaskeva G. , Dinev M. M. , Krasia-Christoforou T. , Turcu R. , Porav S. A. , Balanean F. , Socoliuc V.
Published: March 2020

The preparation procedure of zero magnetic remanence superparamagnetic white paper by means of three-layer membrane configuration (sandwiched structure) is presented. The cellulose acetate fibrous membranes were prepared by electrospinning. The middle membrane layer was magnetically loaded by impregnation with an aqueous ferrofluid of 8 nm magnetic iron oxide nanoparticles colloidally stabilized with a double layer of oleic acid. The nanoparticles show zero magnetic remanence due to their very small diameters and their soft magnetic properties. Changing the ferrofluid magnetic nanoparticle volume fraction, white papers with zero magnetic remanence and tunable saturation magnetization in the range of 0.5–3.5 emu/g were prepared. The dark coloring of the paper owing to the presence of the black magnetite nanoparticles was concealed by the external layers of pristine white cellulose acetate electrospun fibrous membranes.
Beyond Heat Stress: Intestinal Integrity Disruption and Mechanism-Based Intervention Strategies
Authors: Lian Puqiao , Braber Saskia , Garssen Johan , Wichers Harry J. , Folkerts Gert , Fink-Gremmels Johanna , Varasteh Soheil
Published: March 2020

The current climate changes have increased the prevalence and intensity of heat stress (HS) conditions. One of the initial consequences of HS is the impairment of the intestinal epithelial barrier integrity due to hyperthermia and hypoxia following blood repartition, which often results in a leaky gut followed by penetration and transfer of luminal antigens, endotoxins, and pathogenic bacteria. Under extreme conditions, HS may culminate in the onset of “heat stroke”, a potential lethal condition if remaining untreated. HS-induced alterations of the gastrointestinal epithelium, which is associated with a leaky gut, are due to cellular oxidative stress, disruption of intestinal integrity, and increased production of pro-inflammatory cytokines. This review summarizes the possible resilience mechanisms based on in vitro and in vivo data and the potential interventions with a group of nutritional supplements, which may increase the resilience to HS-induced intestinal integrity disruption and maintain intestinal homeostasis.
Social and Economic Factors and Malnutrition or the Risk of Malnutrition in the Elderly: A Systematic Review and Meta-Analysis of Observational Studies
Authors: Besora-Moreno Maria , Llauradó Elisabet , Tarro Lucia , Solà Rosa
Published: March 2020

Malnutrition in the elderly could be tackled by addressing socioeconomic factors. This study aimed to determine the magnitude of the relationship between socioeconomic factors and the malnutrition or malnutrition risk (MR) in the elderly. The PubMed and SCOPUS databases were searched for observational studies that included assessment of malnutrition or/and MR and socioeconomic variables (educational level, living alone, marital status, income and occupational level, feeling of loneliness, place of residence, and food expenditure) in ≥60-year-old subjects, published in English among 2000–2018 (PROSPERO: CRD42019137097). The systematic review included 40 observational studies (34 cross-sectional and 4 cohort studies) and 16 cross-sectional studies in the meta-analysis (34,703 individuals) of malnutrition and MR in relation to low educational level (Odds Ratio (OR): 1.48; 95% Confidence Interval (CI): 1.33–1.64; p < 0.001), living alone (OR: 1.92; 95% CI: 1.73–2.14; p < 0.001), being single, widowed, or divorced (OR: 1.73; 95% CI: 1.57–1.90; p < 0.001), and low income level (OR: 2.69; 95% CI: 2.35–3.08; p < 0.001), and considering these four socioeconomic factors, malnutrition and MR is associated with them (OR: 1.83; 95% CI: 1.73–1.93; p < 0.001). Malnutrition and MR could be reduced by increasing economic level, supporting people living alone or being single, widowed, and divorced, and improving lifelong learning.
Development of a Danish Adapted Healthy Plant-Based Diet Based on the EAT-Lancet Reference Diet
Authors: Lassen Anne D. , Christensen Lene M. , Trolle Ellen
Published: March 2020

Plant-based diets have been linked to both health benefits and a lower climate impact. However, plant-based diets may represent both healthy and unhealthy dietary practices. The present study aimed to develop a nationally adapted healthy plant-based diet based on the global EAT-Lancet reference diet. Development took place in a series of steps. First, the original EAT-Lancet reference diet was evaluated based on food availability, i.e., using Danish food data (Model 1). Then, the model was further modified to reflect national food based dietary guidelines (FBDG) and characteristics of current consumption pattern, e.g., by including processed food, discretionary foods and beverages in the diet (Model 2). The contents of macronutrients, vitamins and minerals, except for vitamin D and iodine, were found to be sufficient for Model 2, according to the recommended nutrient density to be used for planning diets for groups of individuals aged 6–65 years. In addition, the study gave an insight into the nutrients and foods to be aware of in planning a predominantly plant-based diet, thereby providing directions for future revisions of sustainable FBDGs. These include a stronger emphasis on the intake of legumes, nuts and seeds, fruit and vegetables including dark green vegetables, whole-grain products and vegetable oils as well as lowering meat intake.
Into the Deep (Sequence) of the Foot-and-Mouth Disease Virus Gene Pool: Bottlenecks and Adaptation during Infection in Naïve and Vaccinated Cattle
Authors: Fish Ian , Stenfeldt Carolina , Palinski Rachel M. , Pauszek Steven J. , Arzt Jonathan
Published: March 2020

Foot-and-mouth disease virus (FMDV) infects hosts as a population of closely related viruses referred to as a quasispecies. The behavior of this quasispecies has not been described in detail in natural host species. In this study, virus samples collected from vaccinated and non-vaccinated cattle up to 35 days post-experimental infection with FMDV A24-Cruzeiro were analyzed by deep-sequencing. Vaccination induced significant differences compared to viruses from non-vaccinated cattle in substitution rates, entropy, and evidence for adaptation. Genomic variation detected during early infection reflected the diversity inherited from the source virus (inoculum), whereas by 12 days post infection, dominant viruses were defined by newly acquired mutations. Mutations conferring recognized fitness gain occurred and were associated with selective sweeps. Persistent infections always included multiple FMDV subpopulations, suggesting distinct foci of infection within the nasopharyngeal mucosa. Subclinical infection in vaccinated cattle included very early bottlenecks associated with reduced diversity within virus populations. Viruses from both animal cohorts contained putative antigenic escape mutations. However, these mutations occurred during later stages of infection, at which time transmission is less likely to occur. This study improves upon previously published work by analyzing deep sequences of samples, allowing for detailed characterization of FMDV populations over time within multiple hosts.
MoGeo, a Mobile Application to Promote Geotourism in Molise Region (Southern Italy)
Authors: Filocamo Francesca , Di Paola Gianluigi , Mastrobuono Lino , Rosskopf Carmen M.
Published: March 2020

Geotourism represents a powerful and new form of sustainable tourism that has rapidly expanded worldwide over the last decades. To promote it, the use of digital and geomatic tools is becoming of increasing importance. Especially mobile information represents one of the most efficient and smart ways to bring geotourism closer to a wide audience. This applies in particular to rural and inner areas, where the exploitation of geoheritage can represent a crucial resource for eco-friendly and sustainable tourism development. With the aim to promote geotourism on a regional scale, we have implemented a mobile devise application for Molise region, tested in the Alto Molise area. This application, called MoGeo App, aims at providing diversified geotourism information that combines geologic attractions (geosites and geologic itineraries) with other possible tourist attractions (other sites of natural and cultural interest), to respond to differentiated interests and needs of a wide audience. Besides geotourism purposes, the structure of MoGeo App can be used also for other purposes such as educational targets, by adapting contents and language. It appears to be a flexible, easily updatable digital tool, adaptable to various target groups, as well as other regional contexts, both inside and outside of Italy.
Taking the Motion out of Floating Lidar: Turbulence Intensity Estimates with a Continuous-Wave Wind Lidar
Authors: Kelberlau Felix , Neshaug Vegar , Lønseth Lasse , Bracchi Tania , Mann Jakob
Published: March 2020

Due to their motion, floating wind lidars overestimate turbulence intensity ( T I ) compared to fixed lidars. We show how the motion of a floating continuous-wave velocity–azimuth display (VAD) scanning lidar in all six degrees of freedom influences the T I estimates, and present a method to compensate for it. The approach presented here uses line-of-sight measurements of the lidar and high-frequency motion data. The compensation algorithm takes into account the changing radial velocity, scanning geometry, and measurement height of the lidar beam as the lidar moves and rotates. It also incorporates a strategy to synchronize lidar and motion data. We test this method with measurement data from a ZX300 mounted on a Fugro SEAWATCH Wind LiDAR Buoy deployed offshore and compare its T I estimates with and without motion compensation to measurements taken by a fixed land-based reference wind lidar of the same type located nearby. Results show that the T I values of the floating lidar without motion compensation are around 50 % higher than the reference values. The motion compensation algorithm detects the amount of motion-induced T I and removes it from the measurement data successfully. Motion compensation leads to good agreement between the T I estimates of floating and fixed lidar under all investigated wind conditions and sea states.
Can MERRA-2 Reanalysis Data Reproduce the Three-Dimensional Evolution Characteristics of a Typical Dust Process in East Asia? A Case Study of the Dust Event in May 2017
Authors: Yao Wenrui , Che Huizheng , Gui Ke , Wang Yaqiang , Zhang Xiaoye
Published: March 2020

This study used the MERRA-2 reanalysis dataset and ground-based and satellite observational data to comprehensively analyze a typical dust storm event in east Asia on 2–7 May 2017 which engulfed most of China as well as ocean and Japan, and explore the accuracy and comprehensiveness of the MERRA-2 dataset in the analysis of dust processes. The results of comparison show that the description of the spatiotemporal distribution and evolution of the dust aerosols in the dust event using the MERRA-2 data is consistent with the data of AERONET, National Urban Air Quality Real-time Publishing Platform and Hamawari-8. Gobi Deserts was the most influential source area of this dust event with the highest emissions reaching 1.9 × 106 μg/m3. The vertical motion of the atmosphere can lift dust from the source area above 500 hPa. There were low-pressure troughs at 500 and 850 hPa and the winds behind and in front of the trough led to the high-altitude, long-distance transport of dust. Dust gradually affected the northwest China, north China, northeast China, and even the ocean and Japan on 2–7 May. This study demonstrates that although there is some uncertainty about the source of dust emission in the MERRA-2 model, the data accurately simulated the evolution of the dust event and analyze it comprehensively, while the accuracy of simulating the long-term evolution of dust requires further evaluation.
A Machine Learning Framework to Predict Nutrient Content in Valencia-Orange Leaf Hyperspectral Measurements
Authors: Osco Lucas Prado , Ramos Ana Paula Marques , Faita Pinheiro Mayara Maezano , Moriya Érika Akemi Saito , Imai Nilton Nobuhiro , Estrabis Nayara , Ianczyk Felipe , Araújo Fábio Fernando de , Liesenberg Veraldo , Jorge Lúcio André de Castro , Li Jonathan , Ma Lingfei , Gonçalves Wesley Nunes , Marcato Junior José , Eduardo Creste José
Published: March 2020

This paper presents a framework based on machine learning algorithms to predict nutrient content in leaf hyperspectral measurements. This is the first approach to evaluate macro- and micronutrient content with both machine learning and reflectance/first-derivative data. For this, citrus-leaves collected at a Valencia-orange orchard were used. Their spectral data was measured with a Fieldspec ASD FieldSpec® HandHeld 2 spectroradiometer and the surface reflectance and first-derivative spectra from the spectral range of 380 to 1020 nm (640 spectral bands) was evaluated. A total of 320 spectral signatures were collected, and the leaf-nutrient content (N, P, K, Mg, S, Cu, Fe, Mn, and Zn) was associated with them. For this, 204,800 (320 × 640) combinations were used. The following machine learning algorithms were used in this framework: k-Nearest Neighbor (kNN), Lasso Regression, Ridge Regression, Support Vector Machine (SVM), Artificial Neural Network (ANN), Decision Tree (DT), and Random Forest (RF). The training methods were assessed based on Cross-Validation and Leave-One-Out. The Relief-F metric of the algorithms’ prediction was used to determine the most contributive wavelength or spectral region associated with each nutrient. This approach was able to return, with high predictions (R2), nutrients like N (0.912), Mg (0.832), Cu (0.861), Mn (0.898), and Zn (0.855), and, to a lesser extent, P (0.771), K (0.763), and S (0.727). These accuracies were obtained with different algorithms, but RF was the most suitable to model most of them. The results indicate that, for the Valencia-orange leaves, surface reflectance data is more suitable to predict macronutrients, while first-derivative spectra is better linked to micronutrients. A final contribution of this study is the identification of the wavelengths responsible for contributing to these predictions.
Impact of Fire Emissions on U.S. Air Quality from 1997 to 2016–A Modeling Study in the Satellite Era
Authors: Tao Zhining , He Hao , Sun Chao , Tong Daniel , Liang Xin-Zhong
Published: March 2020

A regional modeling system that integrates the state-of-the-art emissions processing (SMOKE), climate (CWRF), and air quality (CMAQ) models has been combined with satellite measurements of fire activities to assess the impact of fire emissions on the contiguous United States (CONUS) air quality during 1997–2016. The system realistically reproduced the spatiotemporal distributions of the observed meteorology and surface air quality, with a slight overestimate of surface ozone (O3) by ~4% and underestimate of surface PM2.5 by ~10%. The system simulation showed that the fire impacts on primary pollutants such as CO were generally confined to the fire source areas but its effects on secondary pollutants like O3 spread more broadly. The fire contribution to air quality varied greatly during 1997-2016 and occasionally accounted for more than 100 ppbv of monthly mean surface CO and over 20 µg m−3 of monthly mean PM2.5 in the Northwest U.S. and Northern California, two regions susceptible to frequent fires. Fire emissions also had implications on air quality compliance. From 1997 to 2016, fire emissions increased surface 8-hour O3 standard exceedances by 10% and 24-hour PM2.5 exceedances by 33% over CONUS.
Assessment of Workflow Feature Selection on Forest LAI Prediction with Sentinel-2A MSI, Landsat 7 ETM+ and Landsat 8 OLI
Authors: Brede Benjamin , Verrelst Jochem , Gastellu-Etchegorry Jean-Philippe , Clevers Jan G. P. W. , Goudzwaard Leo , den Ouden Jan , Verbesselt Jan , Herold Martin
Published: March 2020

The European Space Agency (ESA)’s Sentinel-2A (S2A) mission is providing time series that allow the characterisation of dynamic vegetation, especially when combined with the National Aeronautics and Space Administration (NASA)/United States Geological Survey (USGS) Landsat 7 (L7) and Landsat 8 (L8) missions. Hybrid retrieval workflows combining non-parametric Machine Learning Regression Algorithms (MLRAs) and vegetation Radiative Transfer Models (RTMs) were proposed as fast and accurate methods to infer biophysical parameters such as Leaf Area Index (LAI) from these data streams. However, the exact design of optimal retrieval workflows is rarely discussed. In this study, the impact of five retrieval workflow features on LAI prediction performance of MultiSpectral Instrument (MSI), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) observations was analysed over a Dutch beech forest site for a one-year period. The retrieval workflow features were the (1) addition of prior knowledge of leaf chemistry (two alternatives), (2) the choice of RTM (two alternatives), (3) the addition of Gaussian noise to RTM produced training data (four and five alternatives), (4) possibility of using Sun Zenith Angle (SZA) as an additional MLRA training feature (two alternatives), and (5) the choice of MLRA (six alternatives). The features were varied in a full grid resulting in 960 inversion models in order to find the overall impact on performance as well as possible interactions among the features. A combination of a Terrestrial Laser Scanning (TLS) time series with litter-trap derived LAI served as independent validation. The addition of absolute noise had the most significant impact on prediction performance. It improved the median prediction Root Mean Square Error (RMSE) by 1.08 m2 m−2 when 5% noise was added compared to inversions with 0% absolute noise. The choice of the MLRA was second most important in terms of median prediction performance, which differed by 0.52 m2 m−2 between the best and worst model. The best inversion model achieved an RMSE of 0.91 m2 m−2 and explained 84.9% of the variance of the reference time series. The results underline the need to explicitly describe the used noise model in future studies. Similar studies should be conducted in other study areas, both forest and crop systems, in order to test the noise model as an integral part of hybrid retrieval workflows.
Time-Varying Kelvin Wake Model and Microwave Velocity Observation
Authors: Niu Jie , Liang Xingdong , Zhang Xin
Published: March 2020

In the synthetic aperture radar (SAR) imaging of ship-induced wakes, it is difficult to obtain the Doppler velocity of a Kelvin wake due to the lack of time-varying wake models and suitable radar equipment. The conventional Kelvin wake investigation based on the static Kelvin wake model failed to reflect time-varying characteristics, which are significant in the application of the Kelvin wake model. Therefore, a time-varying Kelvin wake model with consideration of geometric time-varying characteristics and the hydrodynamic equation is proposed in this paper, which reflects the wake’s time-varying change lacking in the conventional Kelvin wake investigation. The Doppler velocity measurement, measured by a specially designed radar, can be exploited to verify the time-varying model by the comparison of velocity fields. Ground-based multi-input multi-output (MIMO) millimeter wave radar imaging through the simultaneous switching of transceiver channels was used to obtain the Doppler velocity for the first time. Finally, promising results have been achieved, which are in good agreement with our proposed model in consideration of the experimental scene. The proposed time-varying model and radar equipment provide velocity measurements for the Kelvin wake observation, which contains huge application potential.
Mitigation of Heat Stress in Solanum lycopersicum L. by ACC-deaminase and Exopolysaccharide Producing Bacillus cereus: Effects on Biochemical Profiling
Authors: Mukhtar Tehmeena , Rehman Shafiq ur , Smith Donald , Sultan Tariq , Seleiman Mahmoud F. , Alsadon Abdullah A. , Amna  , Ali Shafaqat , Chaudhary Hassan Javed , Solieman Talaat H. I. , Ibrahim Abdullah A. , Saad Montasir A. O.
Published: March 2020

Soil microorganisms might be assessed for their capabilities of plant growth promotion in order to identify heat tolerant strategies for crop production. The planned study was conducted to determine the potential of heat tolerant plant growth promoting rhizobacteria (PGPR) in mitigating heat stress effects in tomato. Bacillus cereus was evaluated for plant growth promoting activities and assessed for 1-aminocyclopropane-1-carboxylate (ACC-deaminase) (0.76–C0.9 μM/mg protein/h), and exopolysaccharide (0.66–C0.91 mg/mL) under normal and heat stressed conditions. Plant growth regulators were evaluated through High Performance Liquid Chromatography. Bacterial inoculation effects on important physiological and biochemical parameters were evaluated under normal and heat stressed conditions in growth chamber. The morphological-physiological traits significantly revealed drastic effects on both of un-inoculated tomato varieties under heat stress conditions. Bacterial augmentation significantly promoted shoot, root length, leaf surface area, fresh and dry weight. Heat stress enhanced extracellular polymeric substances (EPS) production and cleavage of ACC into a-ketobutyrate and ammonia due to ACC-deaminase producing bacteria that significantly reduced the adverse effects of heat on tomato growth. In conclusion, the applied plant growth promoting rhizobacteria (PGPR) bacterial strain proved as potential candidate for improving tomato crop growing under heat stressed conditions. However, it is highly suggested to validate the current results by conducting field trials.
RGB Vegetation Indices, NDVI, and Biomass as Indicators to Evaluate C3 and C4 Turfgrass under Different Water Conditions
Authors: Marín José , Yousfi Salima , Mauri Pedro V. , Parra Lorena , Lloret Jaime , Masaguer Alberto
Published: March 2020

Grasslands have a natural capacity to decrease air pollution and a positive impact on human life. However, their maintenance requires adequate irrigation, which is difficult to apply in many regions where drought and high temperatures are frequent. Therefore, the selection of grass species more tolerant to a lack of irrigation is a fundamental criterion for green space planification. This study compared responses to deficit irrigation of different turfgrass mixtures: a C4 turfgrass mixture, Cynodon dactylon-Brachypodium distachyon (A), a C4 turfgrass mixture, Buchloe dactyloides-Brachypodium distachyon (B), and a standard C3 mixture formed by Lolium perenne-Festuca arundinacea-Poa pratensis (C). Three different irrigation regimes were assayed, full irrigated to 100% (FI-100), deficit irrigated to 75% (DI-75), and deficit irrigated to 50% (DI-50) of container capacity. Biomass, normalized difference vegetation index (NDVI), green area (GA), and greener area (GGA) vegetation indices were measured. Irrigation significantly affected the NDVI, biomass, GA, and GGA. The most severe condition in terms of decreasing biomass and vegetation indices was DI-50. Both mixtures (A) and (B) exhibited higher biomass, NDVI, GA, and GGA than the standard under deficit irrigation. This study highlights the superiority of (A) mixture under deficit irrigation, which showed similar values of biomass and vegetation indices under full irrigated and deficit irrigated (DI-75) container capacities.
Temporal Distribution as a Solution for Over-Tourism in Night Tourism: The Case of Suwon Hwaseong in South Korea
Authors: Song Hwasung , Kim Miseong , Park Chanyul
Published: March 2020

As the demands of tourism become increasingly bigger, there are side effects of rapid quantitative growth, representatively, over-tourism. As efforts at minimizing over-tourism, the possibilities of temporal and seasonal distribution were explored. For the experiment, an offline survey was conducted targeting the visitors who visited Suwon Hwaseong, the UNESCO World Heritage in South Korea during the nighttime. Group classification was conducted based on visitors’ preferred times and seasons and estimated the marginal willingness to pay (MWTP) for night tourism activities by these classifications. To compare the MWTP of the groups and examine differences in attributes between the groups, a choice experiment (CE) was used. The results from the CE revealed that the MWTP for attributes was different in those groups. Based on MWTP of each group and their characteristics, it was confirmed that temporal and seasonal distribution can be one solution of over-tourism. These results may be useful for night tourism management and development at a UNESCO World Heritage site, such as providing strategies for minimizing over-tourism, which is distributed by peak and non-peak times.
Probabilistic Assessment of Hybrid Wind-PV Hosting Capacity in Distribution Systems
Authors: Liu Dichen , Wang Chenxu , Tang Fei , Zhou Yixi
Published: March 2020

In recent years, hybrid wind-photovoltaic (PV) systems are flourishing due to their advantages in the utilization of renewable energy. However, the accurate assessment of the maximum integration of hybrid renewable generation is problematic because of the complex uncertainties of source and demand. To address this issue, we develop a stochastic framework for the quantification of hybrid energy hosting capacity. In the proposed framework, historical data sets are adopted to represent the stochastic nature of production and demand. Moreover, extreme combinations of production and demand are introduced to avoid multiple load flow calculations. The proposed framework is conducted in the IEEE 33-bus system to evaluate both single and hybrid energy hosting capacity. The results demonstrate that the stochastic framework can provide accurate evaluations of hosting capacity while significantly reducing the computational burden. This study provides a comprehensive understanding of hybrid wind-PV hosting capacity and verifies the excellent performance of the hybrid energy system in facilitating integration and energy utilization.
The “Metal-Energy-Construction Mineral” Nexus in the Island Metabolism: The Case of the Extractive Economy of New Caledonia
Authors: Bahers Jean-Baptiste , Higuera Paula , Ventura Anne , Antheaume Nicolas
Published: March 2020

The concept of island metabolism strives to implement the principles of social ecology at the island scale. It is, therefore, a question of analyzing the flows of materials and energy passing through these territories, as well as the resource base needed to sustain their activities. We propose to develop a nexus approach to the New Caledonian island metabolism to understand the interactions between biophysical structures and societal, as well as economic, activities. Metals, construction minerals, and energy are good symbols of economies based on the extraction of non-renewable resources. This is why, in this article, we sought to investigate how the “metal-energy-construction mineral” nexus can affect the resilience and metabolic sustainability of the extractive island of New Caledonia. We carried out the Material and Energy Flow Analysis (MEFA) of each nexus subsystem for 2016 and of the nodes of interdependence. We also interrogated the role of importing countries because the island’s metabolism is dominated by the nickel extraction industry. Indeed, the metabolic profile of this island corresponds to the one of a supply territory for other consumption territories. The latter outsource the impacts of their own consumption to New Caledonia. Finally, based on interviews with economic stakeholders, we studied the potential building blocks for the emergence of an industrial symbiosis in the nexus.
Consumer Considerations for the Implementation of Sustainable Packaging: A Review
Authors: Boz Ziynet , Korhonen Virpi , Koelsch Sand Claire
Published: March 2020

Packaging sustainability concepts have co-evolved with the increasing incorporation of the principles of sustainable development at various levels within industrial and organizational platforms. Currently, pollution from plastics, packaging-related waste, declining air, soil, and water quality, climate change, and other contemporary challenges are influencing the packaging industry. Barriers such as value chain complexities and negative consumer attitudes due to the economic, social, and environmental demands of sustainable behaviors can discourage companies from the implementation of more sustainable packaging. Hence, packages with improved sustainability may never make their way into the marketplace. However, the next generation of sustainable solutions can be motivated by efforts that fuel a positive consumer attitude towards sustainable packaging. In order to direct efforts, a clear understanding of consumer dynamics in ecological material preferences, willingness to pay, recycling, and factors impacting sustainable behaviors are essential. The objective of this work is to (i) explore the definitions, the impact of sustainable packaging in the value chain, and consumer behavior theories; (ii) review current practices, factors affecting sustainable behaviors, and consumer testing methods; (iii) present three distinct case studies on consumer preferences and value perceptions on bio-based cellulose materials and the impact of on-label claims and pre-evaluation education in consumer preferences; and (iv) to reveal the research gaps and opportunities for consumer research and suggest strategies for stakeholders to communicate packaging sustainability to consumers.
Simulating and Predicting Crop Yield and Soil Fertility under Climate Change with Fertilizer Management in Northeast China Based on the Decision Support System for Agrotechnology Transfer Model
Authors: Yan Wenting , Jiang Wenting , Han Xiaori , Hua Wei , Yang Jinfeng , Luo Peiyu
Published: March 2020

The risks of climate change and soil degradation for the agricultural environment and crop production are increasingly prominent. Based on the limitations of land resources, it is important to explore a sustainable and effective fertilization strategy to reduce risks and ensure there is a high yield of grain and sustainable development of agriculture. Soil fertility underpins cultivated land, which is the most important resource of agricultural production, and is also the key for maintaining agricultural sustainability. The central elements of soil fertility are soil organic carbon (SOC) and soil nitrogen (SN). This study applied the Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) and the CENTURY-based soil module to simulate the trends of crop yields, SN storages and SOC storages until the end of this century under different climate change circumstances, based on a 36-year long-term experiment established at Shenyang site, China. Four fertilizer practices were applied: control (CK), combined chemical fertilizer of nitrogen, phosphorus, and potassium (NPK), NPK with manure (MNPK), and NPK fertilizers plus a high application rate of manure (hMNPK). The outcomes indicated that the DSSAT model can fully simulate the yields of maize and soybean as well as the dynamic stocks of the SN and SOC. Three Representative Concentration Pathways (RCP 2.6, RCP 4.5, RCP 8.5) for future development were chosen from the fifth assessment report of the United Nations Intergovernmental Panel on Climate Change (IPCC). Moreover, a baseline was installed. Crop yields, SN, and SOC storages from 2016 to 2100 were estimated under four climate scenarios (RCP 2.6, RCP 4.5, RCP 8.5, and Baseline). The RCP scenarios in some treatments reduced SN and SOC stocks and maize yield, and had no effect on soybean yield. However, the application of NPK with manure could improve crop yields, while it increased SN and SOC storages substantially. To some extent, the negative effects of climate scenarios could be mitigated by applying manure. In the RCP 4.5, maize yields of NPK, MNPK, and hMNPK treatments declined by 14.8%, 7.7%, and 6.2%, respectively, compared with that of NPK under Baseline. The NPK fertilizers plus manure treatments could cut the reduction of maize yield caused by climate change in half. Additionally, the SOC storage and SN of chemical fertilizers plus manure treatments under RCP scenarios increased by 20.2%–33.5% and 13.7%–21.7% compared with that of NPK under baseline, respectively. It was concluded that a rational combination of organic and inorganic fertilizer applications is a sustainable and effective agricultural measure to maintain food security and relieve environmental stresses.
Sustainability Research on Promoting the Inheritance of Lacquer Art Based on the E-learning Mode—Case Study of the Popularization of Lacquer Art Education in Primary Schools in Guangzhou Area
Authors: Fan Kuo-Kuang , Li Xue-Hui , Lu Meng-Jia
Published: March 2020

This paper investigates the sustainable inheritance of contemporary lacquer art in the Guangzhou area. Based on the traditional teaching mode dominated by folk inheritance and university education, this paper develops the advantage of contemporary information technology and proposes the application of the e-learning mode to assist the popularization of lacquer art education in society, which plays a positive role in promoting the sustainable development of the lacquer art culture in Guangzhou. This study adopts literature analysis and the questionnaire survey method, and then integrates this learning mode into the lacquer art learning curriculum in primary schools. Finally, this paper summarizes and reflects on the teaching results, and presents the effective role of this model in promoting the teaching of lacquer art culture, which is of important practical significance for consolidating the sustainable development of contemporary lacquer art culture.
Exploring the Use of a Spatio-Temporal City Dashboard to Study Criminal Incidence: A Case Study for the Mexican State of Aguascalientes
Authors: Tapia-McClung Rodrigo
Published: March 2020

By considering public safety as a relevant component of a smart city framework, the development and use of city dashboards that explore the spatio-temporal monitoring of crime incidence to help local governments base their decision-making process on evidence is becoming more relevant. This research deals with the case study of the state of Aguascalientes, Mexico, whose capital hosts the annual San Marcos Fair, considered the most important fair in the country. By developing an online dynamic platform consisting of several different modules that rely on the use of geovisual analytics for dynamic and interactive data display and exploration, authorities can gain insights about the times and locations of the impact of criminal incidence, detect patterns over space and time, and look into what actions could be put in place. This becomes useful in advancing a circular model of the smart city in which urban processes are observed, data is collected and analyzed, management and decision actions occur, and more data is collected to measure their effectiveness. By comparing statistics for the three year period of 2016–2018, it is found that the second year of the study had a significant decrease in pedestrian crime incidence during the Fair, supporting the use of city dashboards with geovisual analytics to help monitor urban processes and aid authorities in making decisions. Further research is needed to uncover more efficient practices to achieve inter-institutional collaboration and data sharing schemes that adhere to and boost the principles of the smart city.
Tackling Traffic Congestion with Workplace Parking Levies
Authors: Santos Georgina , Hagan Anna , Lenehan Orla
Published: March 2020

On the basis of 17 interviews with employers and 272 survey responses from employees, we explore the perceptions of a Workplace Parking Levy (WPL) in Cardiff, with the aim of understanding if a WPL would be an acceptable traffic demand management policy to tackle traffic congestion. We find that employers would not be very supportive of a WPL, whilst employees would, provided employers were to absorb the costs. Despite this support, the majority of those who drive to work would not be prepared to change mode. An important theme throughout the study was the perception of public transport and active travel provision in Cardiff being inadequate. Most study participants felt that investment in public transport and active travel is needed before a WPL is introduced. We conclude that, although a WPL would not be overwhelmingly acceptable to employers and employees, it would be more acceptable than congestion charging, and there is a possibility that acceptability could be increased with the help of feedback from a public consultation.