bluuebunny/crossref_metadata_2025 huggingface dataset:
Coalescence of Binary Droplets in the Transformer Oil Based on Small Amounts of Polymer: Effects of Initial Droplet Diameter and Collision Parameter
Authors: Wang Yiting , Qian Lijuan , Chen Zhongli , Zhou Fang
Published: September 2020

In engineering applications, the coalescence of droplets in the oil phase dominates the efficiency of water-oil separation. To improve the efficiency of water-oil separation, many studies have been devoted to exploring the process of water droplets colliding in the oil phase. In this paper, the volume of fluid (VOF) method is employed to simulate the coalescence of water droplets in the transformer oil based on small amounts of polymer. The influences of the initial diameter and collision parameter of two equal droplets on droplet deformation and coalescence time are investigated. The time evolution curves of the dimensionless maximum deformation diameter of the droplets indicate that the larger the droplet diameter, the more obvious the deformation from central collisions. As the collision parameter increases, the contact area of the two droplets, as well as the kinetic energy that is converted into surface energy, decreases, resulting in an increase in droplet deformation. Furthermore, the effects of the initial droplet diameter and collision parameter on coalescence time are also investigated and discussed. The results reveal that as the initial droplet diameter and collision parameter increase, the droplet coalescence time increases.
Chitosan-Based Aerogel Particles as Highly Effective Local Hemostatic Agents. Production Process and In Vivo Evaluations
Authors: Lovskaya Daria , Menshutina Natalia , Mochalova Maria , Nosov Artem , Grebenyuk Alexander
Published: September 2020

Chitosan aerogels with potential applications as effective local hemostatic agents were prepared using supercritical carbon dioxide drying to preserve the chitosan network structure featuring high internal surfaces and porosities of up to 300 m²/g and 98%, respectively. For the first time, hemostatic efficacy of chitosan-based aerogel particles was studied in vivo on a model of damage of a large vessel in the deep wound. Pigs were used as test animals. It was shown that primary hemostasis was achieved, there were no signs of rebleeding and aerogel particles were tightly fixed to the walls of the wound canal. A dense clot was formed inside the wound (at the femoral artery), which indicates stable hemostasis. This study demonstrated that chitosan-based aerogel particles have a high sorption capacity and are highly effective as local hemostatic agents which can be used to stop massive bleeding.
Effect of Absorbent Foam Filling on Mechanical Behaviors of 3D-Printed Honeycombs
Authors: Yan Leilei , Zhu Keyu , Zhang Yunwei , Zhang Chun , Zheng Xitao
Published: September 2020

Polylactic acid (PLA) hexagonal honeycomb structures were fabricated by using 3D-printing technology. By filling with absorbent polymethacrylimide (PMI) foam, a novel absorbent-foam-filled 3D-printed honeycomb was obtained. The in-plane (L- and W-direction) and out-of-plane (T-direction) compressive performances were studied experimentally and numerically. Due to absorbent PMI foam filling, the elastic modulus, compressive strength, energy absorption per unit volume, and energy absorption per unit mass of absorbent-foam-filled honeycomb under L-direction were increased by 296.34%, 168.75%, 505.57%, and 244.22%, respectively. Moreover, the elastic modulus, compressive strength, energy absorption per unit volume, and energy absorption per unit mass, under W-direction, also have increments of 211.65%, 179.85, 799.45%, and 413.02%, respectively. However, for out-of-plane compression, the compressive strength and energy absorption per unit volume were enhanced, but the density has also been increased; thus, it is not competitive in energy absorption per unit mass. Failure mechanism and dimension effects of absorbent-foam-filled honeycomb were also considered. The approach of absorbent foam filling made the 3D-printed honeycomb structure more competitive in electromagnetic wave stealth applications, while acting simultaneously as load-carrying structures.
Modeling the Adhesion Bonding Strength in Injection Overmolding of Polypropylene Parts
Authors: Giusti Ruggero , Lucchetta Giovanni
Published: September 2020

In this work, the bonding strength of overmolded polypropylene is investigated and modeled. A T-joint specimen was designed to replicate the bonding between a base and an overmolded stem made of the same polymer: a previously molded plaque was used for the base, and the stem was directly overmolded. The effect of melt temperature, holding pressure, and localized heating was investigated following the design of experiments approach. Both the melt and base temperature positively affect the welding strength. On the contrary, the holding pressure negatively contributed, as the crystallization temperature significantly increases with pressure. Then, the bonding strength of the specimens was predicted using a non-isothermal healing model. Moreover, the quadratic distance of diffusion (based on the self-diffusion model) was calculated and correlated with the bonding strength prediction. The non-isothermal healing model well predicts the bonding strength when the reptation time is calculated within the first 0.09 s of the interface temperature evolution. The prediction error ranges from 1% to 35% for the specimens overmolded at high and low melt and base temperatures, respectively.
Method of Selecting Opening Cut Location Using Multi-Criteria Analysis of Decision Variant Mapping
Authors: Kasztelewicz Zbigniew , Sikora Mateusz , Zajączkowski Maciej
Published: September 2020

The aim of the article is to present a solution to the research problem that addresses the selection of the opening cut location in the surface mining method. Selecting the opening cut location is a strategic mine planning matter and has a key impact on the overall processes occurring during mining operations. This choice is a complex, and at the same time, mathematically ill-defined issue. The selection procedure should take into account many, often opposing, perspectives of the interveners, who represent the criteria laid down by the technical and organisational, economic, as well as social and environmental groups. In order to be able to compare criteria of a different nature, the authors implemented a multi-criteria method as a solution, derived from operational research. The mathematical tool best suited to the characteristics of the issue of selecting the opening cut location is a method from the ELECTRE family, which was used to create the final solution ranking. The main achievement of the method presented is the specification of a complementary group of assessment criteria and the application of a method allowing a solution to be created, which results in the selection of the most favourable decision variant. The developed method supports decision-makers responsible for making investment decisions in the implementation of mining projects.
Modality-Free Feature Detector and Descriptor for Multimodal Remote Sensing Image Registration
Authors: Cui Song , Xu Miaozhong , Ma Ailong , Zhong Yanfei
Published: September 2020

The nonlinear radiation distortions (NRD) among multimodal remote sensing images bring enormous challenges to image registration. The traditional feature-based registration methods commonly use the image intensity or gradient information to detect and describe the features that are sensitive to NRD. However, the nonlinear mapping of the corresponding features of the multimodal images often results in failure of the feature matching, as well as the image registration. In this paper, a modality-free multimodal remote sensing image registration method (SRIFT) is proposed for the registration of multimodal remote sensing images, which is invariant to scale, radiation, and rotation. In SRIFT, the nonlinear diffusion scale (NDS) space is first established to construct a multi-scale space. A local orientation and scale phase congruency (LOSPC) algorithm are then used so that the features of the images with NRD are mapped to establish a one-to-one correspondence, to obtain sufficiently stable key points. In the feature description stage, a rotation-invariant coordinate (RIC) system is adopted to build a descriptor, without requiring estimation of the main direction. The experiments undertaken in this study included one set of simulated data experiments and nine groups of experiments with different types of real multimodal remote sensing images with rotation and scale differences (including synthetic aperture radar (SAR)/optical, digital surface model (DSM)/optical, light detection and ranging (LiDAR) intensity/optical, near-infrared (NIR)/optical, short-wave infrared (SWIR)/optical, classification/optical, and map/optical image pairs), to test the proposed algorithm from both quantitative and qualitative aspects. The experimental results showed that the proposed method has strong robustness to NRD, being invariant to scale, radiation, and rotation, and the achieved registration precision was better than that of the state-of-the-art methods.
Parameterization of Vegetation Scattering Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands
Authors: Park Chang-Hwan , Jagdhuber Thomas , Colliander Andreas , Lee Johan , Berg Aaron , Cosh Michael , Kim Seung-Bum , Kim Yoonjae , Wulfmeyer Volker
Published: September 2020

An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for surface and root-zone soil moisture, the latter is retrieved using data assimilation and model support. We found that the RTM based on the tau-omega (τ-ω) model can suffer from significant errors over croplands in the simulation of brightness temperature (Tb) (in average between −9.4K and +12.0K for single channel algorithm (SCA); −8K and +9.7K for dual-channel algorithm (DCA)) if the vegetation scattering albedo (omega) is set constant and temporal variations are not considered. In order to reduce this uncertainty, we propose a time-varying parameterization of omega for the widely established zeroth order radiative transfer τ-ω model. The main assumption is that omega can be expressed by a functional relationship between vegetation optical depth (tau) and the Green Vegetation Fraction (GVF). Assuming allometry in the tau-omega relationship, a power-law function was established and it is supported by correlating measurements of tau and GVF. With this relationship, both tau and omega increase during the development of vegetation. The application of the proposed time-varying vegetation scattering albedo results in a consistent improvement for the unbiased root mean square error of 16% for SCA and 15% for DCA. The reduction for positive and negative biases was 45% and 5% for SCA and 26% and 12% for DCA, respectively. This indicates that vegetation dynamics within croplands are better represented by a time-varying single scattering albedo. Based on these results, we anticipate that the time-varying omega within the tau-omega model will help to mitigate potential estimation errors in the current SMAP soil moisture products (SCA and DCA). Furthermore, the improved tau-omega model might serve as a more accurate observation operator for SMAP data assimilation in weather and climate prediction model.
A Double Epipolar Resampling Approach to Reliable Conjugate Point Extraction for Accurate Kompsat-3/3A Stereo Data Processing
Authors: Oh Jaehong , Han Youkyung
Published: September 2020

Kompsat-3/3A provides along-track and across-track stereo data for accurate three-dimensional (3D) topographic mapping. Stereo data preprocessing involves conjugate point extraction and acquisition of ground control points (GCPs), rational polynomial coefficient (RPC) bias compensation, and epipolar image resampling. Applications where absolute positional accuracy is not a top priority do not require GCPs, but require precise conjugate points from stereo images for subsequent RPC bias compensation, i.e., relative orientation. Conjugate points are extracted between the original stereo data using image-matching methods by a proper outlier removal process. Inaccurate matching results and potential outliers produce geometric inconsistency in the stereo data. Hence, the reliability of conjugate point extraction must be improved. For this purpose, we proposed to apply the coarse epipolar resampling using raw RPCs before the conjugate point matching. We expect epipolar images with even inaccurate RPCs to show better stereo similarity than the original images, providing better conjugate point extraction. To this end, we carried out the quantitative analysis of the conjugate point extraction performance by comparing the proposed approach using the coarsely epipolar resampled images to the traditional approach using the original stereo images. We tested along-track Kompsat-3 stereo and across-track Kompsat-3A stereo data with four well-known image-matching methods: phase correlation (PC), mutual information (MI), speeded up robust features (SURF), and Harris detector combined with fast retina keypoint (FREAK) descriptor (i.e., Harris). These matching methods were applied to the original stereo images and coarsely resampled epipolar images, and the conjugate point extraction performance was investigated. Experimental results showed that the coarse epipolar image approach was very helpful for accurate conjugate point extraction, realizing highly accurate RPC refinement and sub-pixel y-parallax through fine epipolar image resampling, which was not achievable through the traditional approach. MI and PC provided the most stable results for both along-track and across-track test data with larger patch sizes of more than 400 pixels.
Super-Resolution of Sentinel-2 Images Using Convolutional Neural Networks and Real Ground Truth Data
Authors: Galar Mikel , Sesma Rubén , Ayala Christian , Albizua Lourdes , Aranda Carlos
Published: September 2020

Earth observation data is becoming more accessible and affordable thanks to the Copernicus programme and its Sentinel missions. Every location worldwide can be freely monitored approximately every 5 days using the multi-spectral images provided by Sentinel-2. The spatial resolution of these images for RGBN (RGB + Near-infrared) bands is 10 m, which is more than enough for many tasks but falls short for many others. For this reason, if their spatial resolution could be enhanced without additional costs, any posterior analyses based on these images would be benefited. Previous works have mainly focused on increasing the resolution of lower resolution bands of Sentinel-2 (20 m and 60 m) to 10 m resolution. In these cases, super-resolution is supported by bands captured at finer resolutions (RGBN at 10 m). On the contrary, this paper focuses on the problem of increasing the spatial resolution of 10 m bands to either 5 m or 2.5 m resolutions, without having additional information available. This problem is known as single-image super-resolution. For standard images, deep learning techniques have become the de facto standard to learn the mapping from lower to higher resolution images due to their learning capacity. However, super-resolution models learned for standard images do not work well with satellite images and hence, a specific model for this problem needs to be learned. The main challenge that this paper aims to solve is how to train a super-resolution model for Sentinel-2 images when no ground truth exists (Sentinel-2 images at 5 m or 2.5 m). Our proposal consists of using a reference satellite with a high similarity in terms of spectral bands with respect to Sentinel-2, but with higher spatial resolution, to create image pairs at both the source and target resolutions. This way, we can train a state-of-the-art Convolutional Neural Network to recover details not present in the original RGBN bands. An exhaustive experimental study is carried out to validate our proposal, including a comparison with the most extended strategy for super-resolving Sentinel-2, which consists in learning a model to super-resolve from an under-sampled version at either 40 m or 20 m to the original 10 m resolution and then, applying this model to super-resolve from 10 m to 5 m or 2.5 m. Finally, we will also show that the spectral radiometry of the native bands is maintained when super-resolving images, in such a way that they can be used for any subsequent processing as if they were images acquired by Sentinel-2.
Evaluation of a Microwave Emissivity Module for Snow Covered Area with CMEM in the ECMWF Integrated Forecasting System
Authors: Hirahara Yoichi , Rosnay Patricia de , Arduini Gabriele
Published: September 2020

The Community Microwave Emission Modelling platform (CMEM) has been developed by the European Centre for Medium-Range Weather Forecasts (ECMWF) as the forward operator radiative transfer model for low frequency passive microwave brightness temperatures (TB). It is used at ECMWF for L-band TB monitoring over snow free areas. In this paper, upgrades to CMEM are presented in order to explore forward modelling in snow-covered areas for coupled land-atmosphere numerical weather prediction systems. The upgrades enable to use CMEM on an extended range of frequencies and the Helsinki University of Technology multi-layer snow emission model is implemented. Offline CMEM experiments are evaluated against AMSR2 (Advanced Microwave Scanning Radiometer 2) observations showing that simulated TB is improved when using a multi-layer snow scheme, compared to a single-layer scheme. The improvements mainly result from a better representation of snow characteristics in the multi-layer snowpack model. CMEM is also evaluated in the Integrated Forecasting System and coupled to RTTOV (Radiative Transfer for TOVS). The numerical results show improved simulated TB at low frequency V polarization over snow-covered area compared to a configuration using emissivity atlas. Degradations at frequencies higher than 20 GHz indicate that further improvements are required in the emissivity and snowpack properties modelling.
Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data
Authors: Blatchford Megan , M. Mannaerts Chris , Zeng Yijian , Nouri Hamideh , Karimi Poolad
Published: September 2020

This paper analyses the effect of the spatial assessment scale on irrigation performance indicators in small and medium-scale agriculture. Three performance indicators—adequacy (i.e., sufficiency of water use to meet the crop water requirement), equity (i.e., fairness of irrigation distribution), and productivity (i.e., unit of physical crop production/yield per unit water consumption)—are evaluated in five irrigation schemes for three spatial resolutions—250 m, 100 m, and 30 m. Each scheme has varying plot sizes and distributions, with average plot sizes ranging from 0.2 ha to 13 ha. The datasets are derived from the United Nations Food and Agricultural Organization (FAO) water productivity through open access of remotely sensed–derived data (the Water Productivity Open Access Portal—WaPOR) database. Irrigation indicators performed differently in different aspects; for adequacy, all three resolutions show similar spatial trends for relative evapotranspiration (ET) across levels for all years. However, the estimation of relative ET is often higher at higher resolution. In terms of equity, all resolutions show similar inter-annual trends in the coefficient of variation (CV); higher resolutions usually have a higher CV of the annual evapotranspiration and interception (ETIa) while capturing more spatial variability. For productivity, higher resolutions show lower crop water productivity (CWP) due to higher aboveground biomass productivity (AGBP) estimations in lower resolutions; they always have a higher CV of CWP. We find all resolutions of 250 m, 100 m, and 30 m suitable for inter-annual and inter-scheme assessments regardless of plot size. While each resolution shows consistent temporal trends, the magnitude of the trend in both space and time is smoothed by the 100 m and 250 m resolution datasets. This frequently results in substantial differences in the irrigation performance assessment criteria for inter-plot comparisons; therefore, 250 m and 100 m are not recommended for inter-plot comparison for all plot sizes, particularly small plots (<2 ha). Our findings highlight the importance of selecting the spatial resolution appropriate to scheme characteristics when undertaking irrigation performance assessment using remote sensing.
Refining Land-Cover Maps Based on Probabilistic Re-Classification in CCA Ordination Space
Authors: Wan Yue , Zhang Jingxiong , Yang Wenjing , Tang Yunwei
Published: September 2020

Due to spatial inhomogeneity of land-cover types and spectral confusions among them, land-cover maps suffer from misclassification errors. While much research has focused on improving image classification by re-processing source images with more advanced algorithms and/or using images of finer resolution, there is rarely any systematic work on re-processing existing maps to increase their accuracy. We propose refining existing maps to achieve accuracy gains by exploring and utilizing relationships between reference data, which are often already available or can be collected, and map data. For this, we make novel use of canonical correspondence analysis (CCA) to analyze reference-map class co-occurrences to facilitate probabilistic re-classification of map classes in CCA ordination space, a synthesized feature space constrained by map class occurrence patterns. Experiments using GlobeLand30 land-cover (2010) over Wuhan, China were carried out using reference sample data collected previously for accuracy assessment in the same area. Reference sample data were stratified by map classes and their spatial heterogeneity. To examine effects of model-training sample size on refinements, three subset samples (360, 720, and 1480 pixels) were selected from a pool of 3000 sample pixels (the full training sample). Logistic regression modeling was employed as a baseline method for comparisons. Performance evaluation was based on a test sample of 1020 pixels using a strict and relaxed definitions of agreement between reference classification and map classification, resulting in measures of types I and II, respectively. It was found that the CCA-based method is more accurate than logistic regression in general. With increasing sample sizes, refinements generally lead to greater accuracy gains. Heterogeneous sub-strata usually see greater accuracy gains than in homogeneous sub-strata. It was also revealed that accuracy gains in specific strata (map classes and sub-strata) are related to strata refinability. Regarding CCA-based refinements, a relatively small sample of 360 pixels achieved a 3% gain in both overall accuracy (OA) and F0.01 score (II). By using a selective strategy in which only refinable strata of cultivated land and forest are included in refinement, accuracy gains are further increased, with 5–11% gains in users’ accuracies (UAs) (II) and 4–10% gains in F0.01 scores (II). In conclusion, on condition of refinability, map refinement is well worth pursuing, as it increases accuracy of existing maps, extends utility of reference data, facilitates uncertainty-informed map representation, and enhances our understanding about relationships between reference data and map data and about their synthesis.
Retrieval of Crude Protein in Perennial Ryegrass Using Spectral Data at the Canopy Level
Authors: Togeiro de Alckmin Gustavo , Lucieer Arko , Roerink Gerbert , Rawnsley Richard , Hoving Idse , Kooistra Lammert
Published: September 2020

Crude protein estimation is an important parameter for perennial ryegrass (Lolium perenne) management. This study aims to establish an effective and affordable approach for a non-destructive, near-real-time crude protein retrieval based solely on top-of-canopy reflectance. The study contrasts different spectral ranges while selecting a minimal number of bands and analyzing achievable accuracies for crude protein expressed as a dry matter fraction or on a weight-per-area basis. In addition, the model’s prediction performance in known and new locations is compared. This data collection comprised 266 full-range (350–2500 nm) proximal spectral measurements and corresponding ground truth observations in Australia and the Netherlands from May to November 2018. An exhaustive-search (based on a genetic algorithm) successfully selected band subsets within different regions and across the full spectral range, minimizing both the number of bands and an error metric. For field conditions, our results indicate that the best approach for crude protein estimation relies on the use of the visible to near-infrared range (400–1100 nm). Within this range, eleven sparse broad bands (of 10 nm bandwidth) provide performance better than or equivalent to those of previous studies that used a higher number of bands and narrower bandwidths. Additionally, when using top-of-canopy reflectance, our results demonstrate that the highest accuracy is achievable when estimating crude protein on its weight-per-area basis (RMSEP 80 kg.ha−1). These models can be employed in new unseen locations, resulting in a minor decrease in accuracy (RMSEP 85.5 kg.ha−1). Crude protein as a dry matter fraction presents a bottom-line accuracy (RMSEP) ranging from 2.5–3.0 percent dry matter in optimal models (requiring ten bands). However, these models display a low explanatory ability for the observed variability (R2 > 0.5), rendering them only suitable for qualitative grading.
Automatic Generation of Sentinel-1 Continental Scale DInSAR Deformation Time Series through an Extended P-SBAS Processing Pipeline in a Cloud Computing Environment
Authors: Lanari Riccardo , Bonano Manuela , Casu Francesco , Luca Claudio De , Manunta Michele , Manzo Mariarosaria , Onorato Giovanni , Zinno Ivana
Published: September 2020

We present in this work an advanced processing pipeline for continental scale differential synthetic aperture radar (DInSAR) deformation time series generation, which is based on the parallel small baseline subset (P-SBAS) approach and on the joint exploitation of Sentinel-1 (S-1) interferometric wide swath (IWS) SAR data, continuous global navigation satellite system (GNSS) position time-series, and cloud computing (CC) resources. We first briefly describe the basic rationale of the adopted P-SBAS processing approach, tailored to deal with S-1 IWS SAR data and to be implemented in a CC environment, highlighting the innovative solutions that have been introduced in the processing chain we present. They mainly consist in a series of procedures that properly exploit the available GNSS time series with the aim of identifying and filtering out possible residual atmospheric artifacts that may affect the DInSAR measurements. Moreover, significant efforts have been carried out to improve the P-SBAS processing pipeline automation and robustness, which represent crucial issues for interferometric continental scale analysis. Then, a massive experimental analysis is presented. In this case, we exploit: (i) the whole archive of S-1 IWS SAR images acquired over a large portion of Europe, from descending orbits, (ii) the continuous GNSS position time series provided by the Nevada Geodetic Laboratory at the University of Nevada, Reno, USA (UNR-NGL) available for the investigated area, and (iii) the ONDA platform, one of the Copernicus Data and Information Access Services (DIAS). The achieved results demonstrate the capability of the proposed solution to successfully retrieve the DInSAR time series relevant to such a huge area, opening new scenarios for the analysis and interpretation of these ground deformation measurements.
Extraction, Quantification, and Cytokine Inhibitory Response of Bakuchiol in Psoralea coryfolia Linn.
Authors: Khuranna Deepak , Sharma Sanchit , Mir Showkat Rasool , Aqil Mohd , Ahmad Ajaz , Rehman Muneeb U , Ahmad Parvaiz , Alwahibi Mona S. , Elshikh Mohamed Soliman , Mujeeb Mohd
Published: September 2020

(1) Background: The present investigation studies the optimization of extraction, quantification, and cytokine inhibitory effects bakuchiol (BKL) in Psoralea coryfolia Linn. (2) Methods: The seeds of Psoralea coryfolia cleaned, dried, and powdered. Different separation methods maceration, reflux, Soxhlet, and ultrasonic assisted extraction (UAE) were employed for the isolation of BKL by five pure solvents. The quantity of BKL was measured by high-performance liquid chromatography (HPLC) method to determine the highest yield percentage. The effect of optimized BKL was then tested in an animal model of sepsis induced by lipopolysaccharides (LPS). (3) Results: The UAE method was found to be the best among tested separation methods and yielded highest percentage of BKL in petroleum ether extract. Septic rats showed a significant elevation in levels of biochemical markers like AST, ALT, ALP, BIL, SCr, and BUN in plasma. Proinflammatory cytokines (TNF-α and IL-1) levels were also increased in LPS-induced animals. BKL has been found to significantly reverse these elevated levels as compared to the LPS-induced animals. (4) Conclusion: The present results suggest that BKL has positive effects when administered in animals with pathogenic shock by decreasing the circulating levels of biomarkers. Further studies are necessary to explore the clinical implications of such findings.
Keeping the Nazi Menace Out: George Lincoln Rockwell and the Border Control System in Australia and Britain in the Early 1960s
Authors: Smith Evan
Published: September 2020

In the early 1960s, the American Nazi Party leader George Lincoln Rockwell was invited by neo-Nazi groups in Australia and Britain to come to their respective countries. On both occasions, the minister for immigration in Australia and the home secretary in Britain sought to deny Rockwell entry to the country on the grounds that he was not conducive to the public good and threatened disorder. This was done using the border control and visa system that existed in both countries, which allowed the government to exclude from entry certain individuals that were proponents of extreme or “dangerous” political ideologies. In the post-war period, explicit neo-Nazism was seen as a dangerous ideology and was grounds for exclusion of foreigners, even though domestic political parties espousing the same ideology were allowed to exist. Rockwell never came to Australia, but illicitly entered Britain via Ireland in 1962 before being deported, which highlighted potential problems for the British controlling passage across the Irish Sea. Rockwell’s exclusion and deportation also became a touchpoint for future debates in British politics about the denial of entry and deportation of political figures. This article reveals that the Australian and British governments, while allowing far-right organisations to lawfully exist in their countries, also sought to ban the entry of foreign actors who espoused similar politics. This was due to concerns about potential public disorder and violence, but also allowed both governments to portray white supremacism and racial violence as foreign to their own countries.
Impact of CEOs’ Academic Work Experience on Firms’ Innovation Output and Performance: Evidence from Chinese Listed Companies
Authors: Shao Dong , Zhao Shukuan , Wang Shuang , Jiang Hong
Published: September 2020

To date, the effect of the specific type of prior work experience of chief executive officers (CEOs) on innovation and firm performance remains poorly understood. Using upper perspective theory, this study argues that CEOs’ academic work experience affects firms’ innovation output, which in turn determines how research and development (R&D) activities affect firm performance. Analyzing a sample of 1210 Chinese publicly traded firms from 2013–2017, we found that firms with CEOs who were previously associated with universities or research institutions had better innovation output and performance than firms led by CEOs without such background. In addition, we found that former academics spent more on R&D investment, resulting in lower firm performance compared to firms that were not led by CEOs with an academic background. Furthermore, the innovation output was even higher, and performance was inversely reduced for ventures where state ownership is significant.
Examining Spatial Association of Air Pollution and Suicide Rate Using Spatial Regression Models
Authors: Sun Yeran , Chan Ting On , Xie Jing , Sun Xuan , Huang Ying
Published: September 2020

Air pollution can have adverse impacts on both the physical health and mental health of people. Increasing air pollution levels are likely to increase suicide rates, although the causal mechanisms underlying the relationship between pollution exposure and suicidal behaviour are not well understood. In this study, we aimed to further examine the spatial association of air pollution and suicidal behaviour. Specifically, we investigated whether or how PM2.5 levels are spatially associated with the adult suicide rates at the district level across London. As the data used are geospatial data, we used two newly developed specifications of spatial regression models to investigate the spatial association of PM2.5 levels and suicide. The empirical results show that PM2.5 levels are spatially associated with the suicide rates across London. The two models show that PM2.5 levels have a positive association with adult suicide rates over space. An area with a high percentage of White people or a low median household income is likely to suffer from a high suicide rate.
The Impact of a Time Gap on the Process of Building a Sustainable Relationship between Employee and Customer Satisfaction
Authors: Skowron Lukasz , Gąsior Marcin , Sak-Skowron Monika
Published: September 2020

The aim of this paper is to describe the relationships between changes in employee indices (motivation and satisfaction) and customer indices (satisfaction and loyalty) in a single- and multi-term perspective. The article presents the results of primary research conducted in two industries (banking services and shopping centers) during three annual reference periods. The authors used the PLS-SEM method in the analytical process. The results of the research suggest that there is a strong relationship between changes in the areas of employee and customer satisfaction in the studied sectors, with a one-year time shift, which the authors called the “time gap”. In addition, it turned out that the strength of influence of the employee’s motivation level on customers is clearly lower than the strength of influence of the employee satisfaction. The occurrence of a “time gap” between employee and customer processes suggests that any changes introduced in the area of customer service as well as broadly understood human resource management policy need some time to become sustainable—to be noticed by the market and coded in the minds of the recipients of the offer as the new and currently applicable standard. The article makes a successful attempt at a long-term analysis of the relationship between employees and customers, assuming a time delay between both phenomena. As a result of the conducted research, it was possible to operationalize the discussed relationship in terms of strength and direction as well as the time shift.
Internet of Vehicle Empowered Mobile Media Scenarios: In-Vehicle Infotainment Solutions for the Mobility as a Service (MaaS)
Authors: Yu Zhiyuan , Jin Doudou , Song Xiaoxiao , Zhai Chao , Wang Desheng
Published: September 2020

Recently, the commercial potentials and practical values of Mobility as a Service (MaaS) have been witnessed for sustainable development of smart cities in the field of intelligent transportation. Driven by the Internet of Vehicles (IoV), vehicles gradually become mobile living spaces to satisfy diverse demands of occupants, where the media functionalities, scenario scopes, and user engagements can be all expended dramatically. In the era of 5G/B5G, the intelligent connected vehicles are considered as super media because of the improved In-Vehicle Infotainment (IVI). In this paper, relying on the advanced communication and intelligent techniques, we investigate the IoV-based vehicle-mounted media scenarios and construct IVI solutions for the MaaS. Firstly, we propose the characteristics of vehicle-mounted media scenarios and present the IVI evolution from the aspects of hearing, vision and multi-sensory media services. Secondly, we point out the main features and limitations of IoV-based IVI in 3G/4G. Finally, exploring the potential of super media, both the linkage display and IVI collaborative modes in vehicle-centric media scenarios are introduced as IVI solutions for the MaaS in 5G-V2X and beyond, which intend to further improve the audio-visual experiences of occupants and observers in urban environments.
The Relationship between Renewable Energy and Human Development in OECD Countries: A Panel Data Analysis
Authors: Sasmaz Mahmut Unsal , Sakar Emre , Yayla Yunus Emre , Akkucuk Ulas
Published: September 2020

Renewable energy has attracted researcher attention in recent years, and the number of studies conducted on the topic has increased. The importance of renewable energy has increased because certain energy resources are exhaustible and they damage the environment in various ways. Fossil fuel-based energy is the main culprit for environmental damage and lately renewable energy is the main focus as a safe alternative to fossil fuels. However, replacement of fossil fuels by renewables may have a negative impact on human development, even if it has a positive impact on the environment. With this rationale, this study investigates the relationship between renewable energy and human development in 28 OECD (Organization for Economic Cooperation and Development) countries from 1990 to 2017 by using the Westerlund and Edgerton panel cointegration test with structural breaks and the Dumitrescu and Hurlin causality test. The results of the panel data analysis revealed that renewable energy affected human development positively. In addition, the causality test determined the presence of a bidirectional causality relationship between renewable energy and human development. This study is unique in the sense that it is the only study in the literature examining the relationship between human development index and renewable energy for the countries in question. While similar analyses were conducted in the past for different regions or for just one type of renewable energy, no such study has been conducted in this scale with this method. Another differentiating feature of the study is that it demonstrates the bidirectional nature of the study not just the unidirectional causality. Policymakers are advised to invest in renewable energy projects and also create frameworks which provide incentives to the private sector for renewable energy production.
Inner Archipelagos in Sicily. From Culture-Based Development to Creativity-Oriented Evolution
Authors: Carta Maurizio , Ronsivalle Daniele , Lino Barbara
Published: September 2020

When Covid-19 arrived in Europe from the far East, the media and experts in economics and social sciences noticed that it was the expected discontinuity in the socio-economic development process. Really, the current phase has spread since the 1960s, when the application of econometric worldwide-spread development model was going to produce social inequalities, and consumption of physical, social, and cultural resources. Some places in Italy, far from the erosive and urban context and erosive metropolitan areas, are currently isolated seeds of a new cycle of life, because of the local community identity and the strong link between human, cultural, and natural components are currently working together towards a new development model. Starting from a 20-year research about Local Cultural Systems in Sicily, the research group has defined and tested the cultural dimension of development, and affirmed that the transition to a culture-based growth, as defined by UNESCO, should be the solution for overcoming the erosive Anthropocene era. In western Sicily, the Belice Valley is working on cultural transition thanks to relationships between cultural heritage, identity, and settlement network, that we have designed as a Territorial Archipelago. The research demonstrates that local communities will innovate if they rethink the development model and reshape spatial patterns and economic networks focusing on the creativity-driven vision.
The Relationship between Industrial Heritage, Wine Tourism, and Sustainability: A Case of Local Community Perspective
Authors: Andrade-Suárez María , Caamaño-Franco Iria
Published: September 2020

Our research addresses wine tourism as a means of enhancing the heritage and industrial memory of wine. Specifically, it considers winery tours as a form of industrial tourism capable of boosting the sustainable development of winemaking territories. This article explores the significance and perception of wine tourism from the perspective of the local community by examining a specific case: The Port Wine Cellars in Vila Nova de Gaia (Portugal), where tourism and the wine industry are undergoing a greening process, sharing both cultural and commercial ties. The originality of this article lies in the empirical part of the research, which, using quantitative methods based on questionnaires, provides primary data regarding the relationship between sustainability and industrial wine tourism from the perspective of local residents, key agents in the promotion and success of the destination. In general terms, the results statistics obtained through a cluster analysis show that local perception of the impact of wine tourism in Gaia is favorable, and it is considered an element with the capacity to revitalize the economy and also enhance the city’s image. It is also seen as a sustainable option, attributable mainly to economic, cultural, and governance considerations.
Greening Industry in Vietnam: Environmental Management Standards and Resource Efficiency in SMEs
Authors: Fadly Dalia
Published: September 2020

Over the past decade, enterprises have sought to minimize their ecological footprints through cleaner production strategies. Evidence can be gathered to support either the view that adopting environmental management standards (EMS) is a cost burden on firms and is detrimental to competitiveness, or that adopting standards increases savings giving firms competitive advantage in the long run. To resolve this seeming paradox in an emerging country context, the relationship between adopting EMS certificate and resource efficiency is examined empirically using a panel sample of 1333 manufacturing SMEs in Vietnam for the (2011–2013) period. Applying an instrumental variable approach, the results indicate that certification leads to resource savings reflected by less use of electricity, fuel and water for each unit of output. Additionally, there is a heterogeneous effect of certification on the extent of resource saving depending on the sector of operation. The paper also highlights determinants of certificate adoption among SMEs which should be considered in the promotion of environmental certificates, especially in developing countries. To successfully roll out the adoption of environmental certificates on a larger scale, better knowledge among business owners on potential competitive and environmental sustainability gains from EMS must be disseminated.
How Can E-Commerce Businesses Implement Discount Strategies through Social Media?
Authors: Lv Junjie , Wang Zichen , Huang Yuqing , Wang Tong , Wang Yuanzhuo
Published: September 2020

In the context of the global economic downturn caused by COVID-19, e-commerce has become the first choice for people to shop. Many merchants choose to launch promotion activities through some social media platforms. Price discounts can dramatically increase sales volume in social e-commerce due to the interaction of online consumers. It is urgent for e-commerce merchants to learn rules about discount information dissemination in social media, so as to formulate reasonable discount strategies and achieve sustainable business. This paper constructs an evolutionary game model for e-commerce platforms and merchants when they implement promotion strategies through social media, investigates discount information dissemination among consumers under multiple situations by introducing price discount parameters, and further discusses the influence mechanism of discount size and platform reputation on consumers’ purchase behavior. Results show that in low-reputation e-commerce platforms, the price discount is the main motivation to purchase. Consumers’ preference for the high discount is weakened by the increase in platforms’ reputation. Discounts should be set according to the different reputations. Businesses in a high-reputation environment are relatively more profitable. E-commerce businesses should work together, apply reasonable pricing, and improve their quality to create a green and healthy shopping environment, in order to get benefits and sustainable development.
Examining the Moderating Effects of Green Marketing and Green Psychological Benefits on Customers’ Green Attitude, Value and Purchase Intention
Authors: Liao Ying-Kai , Wu Wann-Yih , Pham Thi-That
Published: September 2020

The purpose of this study is to integrate the theoretical base of green purchasing by using the signaling theory approach to green marketing. Since previous studies do not combine relevant factors from the perspective of Signaling Theory and Attitude-Behavior-Context (ABC) Theory for green purchase, this study attempts to examine the effects of green customer value and attitude towards green products on green purchase intention. Moreover, it aims to identify the moderating effects of green marketing and green psychological benefits on the relationships between customer value, attitude, and green purchase intention. This study involved a survey that comprised 319 customers with at least a year’s experience in buying green products in Cambodia. The findings empirically revealed a significant and positive influence of green customer value on attitude towards green products. Furthermore, both green customer value and attitudes towards green products have a positive effect on green purchase intention. Green marketing (environmental advertising, and green word-of-mouth) and green psychological benefits (warm glow, self-expressive benefits, and nature experience) moderate the relationships between customer value, attitude towards the green product, and green purchase intention. The results may be beneficial for managers and marketers to develop appropriate green marketing strategies. They may also be helpful for academicians to conduct further validations regarding the theoretical framework of green purchasing.