bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vivo Stability of Polyurethane-Based Electrospun Vascular Grafts in Terms of Chemistry and Mechanics
Authors: Gostev Alexander , Shundrina Inna , Pastukhov Vitaliy , Shutov Alexey , Chernonosova Vera , Karpenko Andrey , Laktionov Pavel
Published: April 2020

The biostability of the polyurethanes Tecoflex EG-80A and Pellethane 2363-80A, used as basic polymers of the vascular grafts (VGs) produced by electrospinning, as well as the tensile strength of Tecoflex VGs, are studied. Solutions of Tecoflex or Pellethane with gelatin and bivalirudin in 1,1,1,3,3,3-hexafluoroisopropanol are used for VG production. After 1, 12, and 24 weeks of VG implantation in the infrarenal position of the abdominal aorta of Wistar rats, VGs are explanted, fixed in formalin, freed from outer tissues, dialyzed, and dried. The polyurethanes are extracted from VGs by dispersion/extraction in tetrahydrofuran (THF) and freed from the excess of THF-insoluble biopolymers. The stability of polyurethanes is assessed by IR spectroscopy and gel permeation chromatography. Pellethane has emerged to be stable at all experimental points. Tecoflex loses approximately 10% of its molecular weight (both Mn and Mw) after 3 months and restored its initial value within 6 months of its functioning as a graft. Mechanical testing demonstrates a 30% reduction in the tensile strength after 3 months in VG and a 10% increase after 6 months. The stability and mechanical properties of polyurethane-based VGs demonstrate their utility for the reconstitution of damaged arteries.
Production and Characterization of Large-Scale Recycled Newspaper Enhanced HDPE Composite Laminates
Authors: Zheng Binwei , Guan Litao , Zhang Weiwei , Gu Jin , Tu Dengyun , Hu Chuanshuang
Published: April 2020

Recycled newspaper (NP)/high density polyethylene (HDPE) laminated composite can reach the physical and mechanical criteria for most industrial applications, which shows the potential of using solid-state waste paper in engineering materials. Herein, the effects of splicing pattern and size on the physical and mechanical properties of the laminated composite were investigated with the ultimate purpose to fabricate a large-scaleale composite. The laminated composite with a stair-like splicing had better physical and mechanical properties than that with a vertical splicing. An efficient stress transfer could be guaranteed when the distance between the two adjacent junctions were greater than a critical proportion of 1/32 of the length at longitudinal direction. The tensile and flexural properties of the large-scaleale composite with a stair-like splicing, which was fabricated at the splicing ratio of 1/32, were 109 ± 4.2 MPa (MOR), 9836 ± 411 MPa (MOE), 119 ± 7.1 MPa (MOR) and 10002 MPa ± 347 (MOE).
Biorefining Oat Husks into High-Quality Lignin and Enzymatically Digestible Cellulose with Acid-Catalyzed Ethanol Organosolv Pretreatment
Authors: Chopda Rushab , Ferreira Jorge A. , Taherzadeh Mohammad J.
Published: April 2020

Oat husks are low-value lignocellulosic residues of oat processing that carry an environmental impact. Their polymers (cellulose, hemicellulose, and lignin) can be converted into a wide variety of value-added products; however, efficient pretreatment methods are needed that allow their fine separation for further tailored valorization. This study pioneered the use of milling-free and low acid-catalyzed ethanol organosolv for the delignification of oat husks, allowing their conversion into three high-quality streams, namely, glucan-rich, lignin-rich, and hemicellulosic compound-rich streams. Temperature, retention time, and solid-to-liquid ratio were found to impact the delignification of oat husks when using a one-factor-at-a-time strategy. The ideal conditions that were found (210 °C, 90 min, and solid-to-liquid ratio of 1:2) culminated into glucan and lignin fractions containing 74.5% ± 11.4% glucan and 74.9% ± 7.6% lignin, respectively. These high-purity lignin fractions open the possibility for higher value applications by lignin, potentially impacting the feasibility of second generation biorefineries. The glucan fraction showed 90% digestibility after 48 h of hydrolysis with 10 filter paper units of enzyme cocktail per gram of glucan. Considering the absence of size reduction and high solid loading, together with the quality of the obtained streams, organosolv pretreatment could be a potential strategy for the valorization of oat lignocellulosic residues.
Attaining Post-Conflict Peace Using the jus post bellum Concept
Authors: Klein Albert W.
Published: April 2020

To attain peace after state-on-state war, there must be a belligerent occupation to establish control and security of a defeated state—but that is not enough. There is the concept of jus post bellum concerning the vanquished, which is critically necessary in practice, yet insufficiently developed and understood. Providing the history and tentatively trying to determine the elements that are contained in this concept are the present article’s purpose. Tracing the concept from the earliest Christian writers to the more secular present-day authors will aid in the prospective application of jus post bellum. Scholars, military officers, statesmen, religious leaders, and humanitarians need to understand and accept the basic elements of the concept. A clear understanding of the largely religious history behind these elements should assist in their acceptance and future practical application, once these are agreed upon.
Gap Fill of Land Surface Temperature and Reflectance Products in Landsat Analysis Ready Data
Authors: Zhou Qiang , Xian George , Shi Hua
Published: April 2020

The recently released Landsat analysis ready data (ARD) over the United States provides the opportunity to investigate landscape dynamics using dense time series observations at 30-m resolution. However, the dataset often contains data gaps (or missing data) because of cloud contamination or data acquisition strategy, which result in different capabilities for seasonality modeling. We present a new algorithm that focuses on data gap filling using clear observations from orbit overlap regions. Multiple linear regression models were established for each pixel time series to estimate stable predictions and uncertainties. The model’s training data came from stratified random samples based on the time series similarity between the pixel and data from the overlap regions. The algorithm was first evaluated using four tiles (5000 × 5000 30-m pixels for each tile) from 2018 land surface temperature data (LST) in Atlanta, Georgia. The accuracy was assessed using randomly masked clear observations with an average Root Mean Square Error (RMSE) of 3.88 and an average bias of −0.37, which were comparable to the product accuracy. We also applied the method on ARD surface reflectance bands at Fairbanks, Alaska. The accuracy assessment suggested a majority RMSE of less than 0.04 and a bias of less than 0.0023. The gap-filled time series can be of help for reliable seasonal modeling and reducing artifacts related to data availability. This approach can also be applied to other datasets, vegetation indexes, or spectral reflectance bands of other sensors.
Soil Color and Mineralogy Mapping Using Proximal and Remote Sensing in Midwest Brazil
Authors: Poppiel Raúl Roberto , Lacerda Marilusa Pinto Coelho , Rizzo Rodnei , Safanelli José Lucas , Bonfatti Benito Roberto , Silvero Nélida Elizabet Quiñonez , Demattê José Alexandre Melo
Published: April 2020

Soil color and mineralogy are used as diagnostic criteria to distinguish different soil types. In the literature, 350–2500 nm spectra were successfully used to predict soil color and mineralogy, but these attributes currently are not mapped for most Brazilian soils. In this paper, we provided the first large-extent maps with 30 m resolution of soil color and mineralogy at three depth intervals for 850,000 km2 of Midwest Brazil. We obtained soil 350–2500 nm spectra from 1397 sites of the Brazilian Soil Spectral Library at 0–20 cm, 20–60, and 60–100 cm depths. Spectra was used to derive Munsell hue, value, and chroma, and also second derivative spectra of the Kubelka–Munk function, where key spectral bands were identified and their amplitude measured for mineral quantification. Landsat composites of topsoil and vegetation reflectance, together with relief and climate data, were used as covariates to predict Munsell color and Fe–Al oxides, and 1:1 and 2:1 clay minerals of topsoil and subsoil. We used random forest for soil modeling and 10-fold cross-validation. Soil spectra and remote sensing data accurately mapped color and mineralogy at topsoil and subsoil in Midwest Brazil. Hematite showed high prediction accuracy (R2 > 0.71), followed by Munsell value and hue. Satellite topsoil reflectance at blue spectral region was the most relevant predictor (25% global importance) for soil color and mineralogy. Our maps were consistent with pedological expert knowledge, legacy soil observations, and legacy soil class map of the study region.
Landsat Images Classification Algorithm (LICA) to Automatically Extract Land Cover Information in Google Earth Engine Environment
Authors: Capolupo Alessandra , Monterisi Cristina , Tarantino Eufemia
Published: April 2020

Remote sensing has been recognized as the main technique to extract land cover/land use (LC/LU) data, required to address many environmental issues. Therefore, over the years, many approaches have been introduced and explored to optimize the resultant classification maps. Particularly, index-based methods have highlighted its efficiency and effectiveness in detecting LC/LU in a multitemporal and multisensors analysis perspective. Nevertheless, the developed indices are suitable to extract a specific class but not to completely classify the whole area. In this study, a new Landsat Images Classification Algorithm (LICA) is proposed to automatically detect land cover (LC) information using satellite open data provided by different Landsat missions in order to perform a multitemporal and multisensors analysis. All the steps of the proposed method were implemented within Google Earth Engine (GEE) to automatize the procedure, manage geospatial big data, and quickly extract land cover information. The algorithm was tested on the experimental site of Siponto, a historic municipality located in Apulia Region (Southern Italy) using 12 radiometrically and atmospherically corrected satellite images collected from Landsat archive (four images, one for each season, were selected from Landsat 5, 7, and 8, respectively). Those images were initially used to assess the performance of 82 traditional spectral indices. Since their classification accuracy and the number of identified LC categories were not satisfying, an analysis of the different spectral signatures existing in the study area was also performed, generating a new algorithm based on the sequential application of two new indices (SwirTirRed (STRed) index and SwiRed index). The former was based on the integration of shortwave infrared (SWIR), thermal infrared (TIR), and red bands, whereas the latter featured a combination of SWIR and red bands. The performance of LICA was preferable to those of conventional indices both in terms of accuracy and extracted classes number (water, dense and sparse vegetation, mining areas, built-up areas versus water, and dense and sparse vegetation). GEE platform allowed us to go beyond desktop system limitations, reducing acquisition and processing times for geospatial big data.
Super-Resolution for Hyperspectral Remote Sensing Images Based on the 3D Attention-SRGAN Network
Authors: Dou Xinyu , Li Chenyu , Shi Qian , Liu Mengxi
Published: April 2020

Hyperspectral remote sensing images (HSIs) have a higher spectral resolution compared to multispectral remote sensing images, providing the possibility for more reasonable and effective analysis and processing of spectral data. However, rich spectral information usually comes at the expense of low spatial resolution owing to the physical limitations of sensors, which brings difficulties for identifying and analyzing targets in HSIs. In the super-resolution (SR) field, many methods have been focusing on the restoration of the spatial information while ignoring the spectral aspect. To better restore the spectral information in the HSI SR field, a novel super-resolution (SR) method was proposed in this study. Firstly, we innovatively used three-dimensional (3D) convolution based on SRGAN (Super-Resolution Generative Adversarial Network) structure to not only exploit the spatial features but also preserve spectral properties in the process of SR. Moreover, we used the attention mechanism to deal with the multiply features from the 3D convolution layers, and we enhanced the output of our model by improving the content of the generator’s loss function. The experimental results indicate that the 3DASRGAN (3D Attention-based Super-Resolution Generative Adversarial Network) is both visually quantitatively better than the comparison methods, which proves that the 3DASRGAN model can reconstruct high-resolution HSIs with high efficiency.
Extracting Agricultural Fields from Remote Sensing Imagery Using Graph-Based Growing Contours
Authors: Wagner Matthias P. , Oppelt Natascha
Published: April 2020

Knowledge of the location and extent of agricultural fields is required for many applications, including agricultural statistics, environmental monitoring, and administrative policies. Furthermore, many mapping applications, such as object-based classification, crop type distinction, or large-scale yield prediction benefit significantly from the accurate delineation of fields. Still, most existing field maps and observation systems rely on historic administrative maps or labor-intensive field campaigns. These are often expensive to maintain and quickly become outdated, especially in regions of frequently changing agricultural patterns. However, exploiting openly available remote sensing imagery (e.g., from the European Union’s Copernicus programme) may allow for frequent and efficient field mapping with minimal human interaction. We present a new approach to extracting agricultural fields at the sub-pixel level. It consists of boundary detection and a field polygon extraction step based on a newly developed, modified version of the growing snakes active contours model we refer to as graph-based growing contours. This technique is capable of extracting complex networks of boundaries present in agricultural landscapes, and is largely automatic with little supervision required. The whole detection and extraction process is designed to work independently of sensor type, resolution, or wavelength. As a test case, we applied the method to two regions of interest in a study area in the northern Germany using multi-temporal Sentinel-2 imagery. Extracted fields were compared visually and quantitatively to ground reference data. The technique proved reliable in producing polygons closely matching reference data, both in terms of boundary location and statistical proxies such as median field size and total acreage.
Untangling the Incoherent and Coherent Scattering Components in GNSS-R and Novel Applications
Authors: Munoz-Martin Joan Francesc , Onrubia Raul , Pascual Daniel , Park Hyuk , Camps Adriano , Rüdiger Christoph , Walker Jeffrey , Monerris Alessandra
Published: April 2020

As opposed to monostatic radars where incoherent backscattering dominates, in bistatic radars, such as Global Navigation Satellite Systems Reflectometry (GNSS-R), the forward scattered signals exhibit both an incoherent and a coherent component. Current models assume that either one or the other are dominant, and the calibration and geophysical parameter retrieval (e.g., wind speed, soil moisture, etc.) are developed accordingly. Even the presence of the coherent component of a GNSS reflected signal itself has been a matter of discussion in the last years. In this work, a method developed to separate the leakage of the direct signal in the reflected one is applied to a data set of GNSS-R signals collected over the ocean by the Microwave Interferometer Reflectometer (MIR) instrument, an airborne dual-band (L1/E1 and L5/E5a), multi-constellation (GPS and Galileo) GNSS-R instrument with two 19-elements antenna arrays with 4 beam-steered each. The presented results demonstrate the feasibility of the proposed technique to untangle the coherent and incoherent components from the total power waveform in GNSS reflected signals. This technique allows the processing of these components separately, which increases the calibration accuracy (as today both are mixed and processed together), allowing higher resolution applications since the spatial resolution of the coherent component is determined by the size of the first Fresnel zone (300–500 meters from a LEO satellite), and not by the size of the glistening zone (25 km from a LEO satellite). The identification of the coherent component enhances also the location of the specular reflection point by determining the peak maximum from this coherent component rather than the point of maximum derivative of the incoherent one, which is normally noisy and it is blurred by all the glistening zone contributions.
Dynamic Modal Identification of Telecommunication Towers Using Ground Based Radar Interferometry
Authors: Nico Giovanni , Prezioso Giuseppina , Masci Olimpia , Artese Serena
Published: April 2020

This work presents a methodology to monitor the dynamic behaviour of tall metallic towers based on ground-based radar interferometry, and apply it to the case of telecommunication towers. Ground-based radar displacement measurements of metallic towers are acquired without installing any Corner Reflector (CR) on the structure. Each structural element of the tower is identified based on its range distance with respect to the radar. The interferometric processing of a time series of radar profiles is used to measure the vibration frequencies of each structural element and estimate the amplitude of its oscillation. A methodology is described to visualize the results and provide a useful tool for the real-time analysis of the dynamic behaviour of metallic towers.
On-Board Wind Scatterometry
Authors: Xu Xingou , Dong Xiaolong , Xie Yu
Published: April 2020

Real-time (RT) ocean surface wind can make key improvements to disaster alarmingand safety of maritime navigation to avoid loss in property and human lives. Wind scatterometry is a well-acquainted way of obtaining good quality ocean surface winds, and it has been in application for decades. Existing wind-obtaining chains employ ground stations for receiving observations and can, at best, provide products in around 30 minutes for limited regions. In recent years, a satellite information-obtaining and transmission network is the new trend of Earth observation. In this research, on-board wind retrieval environment and procedures, which are different from traditional wind-obtaining chains, are proposed. First, the establishment of the on-board environment is instructed. Structures of each module are provided. The ground simulation system is been established based on this. After that, existing observing and processing routines of wind scatterometry are described, and then an on-board processing chain proposed and described. Modifications to existing satellite-ground chains are highlighted. The proposed method is validated in Level 0 data from the Chinese–French Oceanic SATellite (CFOSAT). Experiments indicate that the proposed on-board processing procedure can provide comparable results to ground-processed wind products. The root-mean-square error (RMSE) of wind speed for a track of data used in the experiment was about 0.26 m/s, and it was about 0.8° for wind direction. By decreasing wind field result quality, calculation time can be lessened in the on-board environment. However, it is found that in the whole chain of on-board wind generation, the most time-consuming procedure is observation-obtaining. The proposed on-board processing method can achieve good wind accuracy while meeting RT applications with good processing time. This provides a good complement to existing on-board-observing-ground-processing chains for RT applications.
The Influence of Housing Investment on Urban Innovation: An Empirical Analysis Based on City-Level Panel Data in China
Authors: Wang Xiaojie , Duan Yi , Liu Pengcheng , Han Guixin
Published: April 2020

The reasonable control of housing investment and the encouragement of innovation are two major tasks for the Chinese government. This article uses city-level urban panel data over 2001-2015 to study the effect of housing investment on urban innovation in China. The full-sample regression result shows that housing investment inhibits urban innovation. Housing investment can curb urban capital flow and reduce the gross profits of enterprises, which can hinder the improvement of urban innovation. As for different regions, the eastern region has been more obviously influenced by housing investment, while it has led to less influence on the middle and western regions in China. The conclusions of this study can help to clarify the internal relationship between housing investment and urban innovation, identify how to promote the current transformation and upgrading of China’s real estate investment, and improve the vitality of the real economy.
What Hinders the Promotion of the Green Mining Mode in China? A Game-Theoretical Analysis of Local Government and Metal Mining Companies
Authors: Zhao Yuan , Zhao Guoyan , Zhou Jing , Pei Dianfei , Liang Weizhang , Qiu Ju
Published: April 2020

China is currently trying to reduce the environmental impact of metal mining operations by promoting green mining. However, conflicts of interest between the central government, local governments, and metal mining companies often negatively affect the implementation of related policies. This paper conducted a theoretical analysis of the game mechanism between local governments and metal mining companies to study the factors that influence their strategies. First, we summarize the various game model parameters, determine the strategies which the companies and local government can choose, and establish the game model for the companies and the local government. Second, we list the utility of the company and local government under all game outcomes and analyse their behavioral tendencies. Third, we discuss the impacts of various factors on the choice of their mining mode in detail. The behavioral analysis shows that the local government’s inclination to supervise a mine is negatively related to the supervision cost and positively related to the production scale of this mine; various factors influence the companies in their decision making, with the yield and comprehensive utilization rate of tailings and waste rocks have the greatest impact; the scale of mine production also affects the companies’ willingness to carry out technological innovation. Finally, we offer some suggestions for the promotion of green mining.
Linking Changes in Land Cover and Land Use of the Lower Mekong Basin to Instream Nitrate and Total Suspended Solids Variations
Authors: Ly Kongmeng , Metternicht Graciela , Marshall Lucy
Published: April 2020

Population growth and economic development are driving changes in land use/land cover (LULC) of the transboundary Lower Mekong River Basin (LMB), posing a serious threat to the integrity of the river system. Using data collected on a monthly basis over 30 years (1985–2015) at 14 stations located along the Lower Mekong river, this study explores whether spatiotemporal relationships exist between LULC changes and instream concentrations of total suspended solids (TSS) and nitrate—as proxies of water quality. The results show seasonal influences where temporal patterns of instream TSS and nitrate concentrations mirror patterns detected for discharge. Changes in LULC influenced instream TSS and nitrate levels differently over time and space. The seasonal Mann–Kendall (SMK) confirmed significant reduction of instream TSS concentrations at six stations (p < 0.05), while nitrate levels increased at five stations (p < 0.05), predominantly in stations located in the upper section of the basin where forest areas and mountainous topography dominate the landscape. Temporal correlation analyses point to the conversion of grassland (r = −0.61, p < 0.01) to paddy fields (r = 0.63, p < 0.01) and urban areas (r = 0.44, p < 0.05) as the changes in LULC that mostly impact instream nitrate contents. The reduction of TSS appears influenced by increased forest land cover (r = −0.72, p < 0.01) and by the development and operation of hydropower projects in the upper Mekong River. Spatial correlation analyses showed positive associations between forest land cover and instream concentrations of TSS (r = 0.64, p = 0.01) and nitrate (r = 0.54, p < 0.05), indicating that this type of LULC was heavily disturbed and harvested, resulting in soil erosion and runoff of nitrate rich sediment during the Wet season. Our results show that enhanced understanding of how LULC changes influence instream water quality at spatial and temporal scales is vital for assessing potential impacts of future land and water resource development on freshwater resources of the LMB.
Assessment of the Profitability of Environmental Activities in Forestry
Authors: Zamula Iryna , Tanasiieva Maryna , Travin Vitalii , Nitsenko Vitalii , Balezentis Tomas , Streimikiene Dalia
Published: April 2020

The paper presents a framework for the financial analysis of the environmental measures (programmes) for forestry enterprises. The indicators of the economic and social effectiveness of environmental measures are discussed. The prospects for their implementation in the context of sustainable forest management in Ukraine are analysed. The research focuses on the effectiveness of environmental measures at the level of forestry enterprise. The proposed framework allows for determining the economic and social effectiveness of environmental measures at the enterprise level. To this end, the net discounted income is used to measure the profitability of environmental measures. The payback period is determined to provide an intuition behind the decision to participate in the environmental measures. The proposed framework allows for improving decision support for the national sustainable forestry development programmes not only at the macro level, but also at the level of enterprises.
The Smart Classroom as a Means to the Development of ESD Methodologies
Authors: Cebrián Gisela , Palau Ramon , Mogas Jordi
Published: April 2020

Educational institutions are envisioned as principal agents for addressing the current sustainability challenge that society is facing. Education for Sustainable Development (ESD) is transformational and concerns learning content and outcomes, pedagogy and the learning environment in itself. ESD entails rethinking the learning environment (physical and virtual) in line with sustainable development, which implies classrooms’ transformation towards learner engagement, formative assessments and active methodologies. This paper responds to this need through exploring the relationship between Smart Classrooms and four widely used ESD methodologies (project or problem-based learning, case study, simulation and cooperative inquiry), identifying how the dimensions and categories of the characteristics of Smart Classrooms can contribute and lead to the implementation of ESD methodologies in real teaching practice in an effective way. The method used in this study consisted of a literature review of both theoretical frameworks separately, ESD and Smart Classrooms, and a subsequent expert analysis to identify the interrelation between both. The Smart Classroom shows a high level of adequacy for using problem and project-based learning, case study and cooperative inquiry methods because of its characteristics in terms of technology developments, environmental conditions and processes. Simulation is the ESD methodology with the lowest level of adequacy in a Smart Classroom, because it is primarily held online rather than through face-to-face teaching. Smart Education facilitates the putting in practice of ESD processes as it enables the creation of intelligent, sustainable, resource-efficient, personalised and adaptive learning environments. Further empirical research is needed to explore the influence that the Smart Classroom has in enabling ESD processes and practices, and to identify students’ and teachers’ needs at different education levels. Additionally, teacher training programmes focused on the correct use of Smart Classrooms and on the digital competence of teachers are critical to its successful implementation.
The Negative Perceptions of Apartment Culture as Represented in Korean Films during the 1970s–1990s
Authors: Moon Guen-Jong
Published: April 2020

Popular films, which are cultural products, inevitably reflect the social and architectural culture of the time and the thoughts and interests of the public. This study analyzes the negative perceptions of apartment culture to verify how the negative characteristics of apartment housing were recognized by the general Korean public in a socio-cultural manner. For the analysis, a pool of artistically and publicly renowned Korean films between 1970 and 1999 was constructed. Through the scenes and their respective scripts, the characters, stories, cinematic messages, and architectural spaces were analyzed. The 1970s and 1980s films shed light on the large-scale, uniformly developed apartment complexes to reveal apartments as lonely, anonymous, closed spaces of the urban middle class. During the 1980s–1990s, the negative aspects of apartment developments were highlighted. These include a loss of place and memory, the disintegration of family, the deepening of relative poverty, and standardized desolated scenery. Negative perceptions toward apartments intensified in the 1990s to reveal a lack of communication between neighbors, externality, misunderstanding, and distrust. By diagnosing the Korean public’s negative view of apartments, this study will help find a better housing culture and the positive sustainability of apartments.
How to Transform Sustainable Energy Technology into a Unicorn Start-Up: Technology Review and Case Study
Authors: Lee Dasheng , Lin Kuan-Chung
Published: April 2020

Renewable and sustainable energy technologies must undergo commercialization before contributing to people’s sustainable development. Among different approaches, commercialization to become unicorn start-ups has attracted considerable attention. Unicorn start-ups are companies achieving a valuation of over US$1 billion before launching initial public offerings. Herein, a company adopting solid oxide fuel cells as its single product and becoming a unicorn start-up is considered the case company (Company B). Established in 2001, Company B accumulated US$825.7 million of actual funding and a peak valuation of US$2.9 billion before being publicly listed. After being listed in July 2018, Company B achieved unicorn start-up status. Searching ScienceDirect Online and the IEEE/IET Electronic Library, this. study collects reviews of fuel cell technology development trends. From CB insights, the study collects the timing and amount of funding received by fuel cell-related unicorn start-ups worldwide. The Derwent Innovation (DI) tool is employed to analyze the status of fuel cell-related patent applications of these unicorn start-ups. This study integrates technology review, business status, and patent application data for analysis. Unlike previous technology reviews focusing on researches and developments, this study emphasizes the analysis of intellectual-property-based (IP-based) commercialization strategies. Specifically, it analyzes key factors explaining how a company producing solid oxide fuel cells could transform into a unicorn start-up. These factors are compiled into a ladder framework to provide a reference. Five quantitative indices are promoted. From the managerial point of view, this framework provides an executable guideline for effectively transforming sustainable energy technology into a high-valuation unicorn start-up.
Does Chinese Inward Foreign Direct Investment Improve the Productivity of Domestic Firms? Horizontal Linkages and Absorptive Capacities: Firm-Level Evidence from Ethiopia
Authors: Negash Engidaw Sisay , Zhu Wenjie , Lu Yangyang , Wang Zhikai
Published: April 2020

Publicized as a global call for action in 2015, the United Nations General Assembly (UNGA) has forwarded an agenda of resolutions to achieve the goals of sustainable development by 2030 (SDGs). Due to the specific challenges of funding gaps and the lack of advanced technology, the majority of Sub-Saharan African (SSA) countries are still behind the standard of world development. Since foreign direct investment (FDI) has the potential to bring much-needed capital and efficient technology, FDI has often been considered as a vigorous source of development, even for sustainable development for under-developing economies experienced today. Conspicuously, Chinese outward FDI (OFDI) into SSA has seen a strong upward trend in the 21st Century, after China proclaimed its “go global” strategy. Ethiopia is one of the favored destinations of the trend of Chinese OFDI, which also substantially continues through the SSA region. The hosting economy of Ethiopia expected that Chinese inward FDI comes with capital, efficient technology, and knowledge to contribute innovations through directly improving productivity and competitiveness via technological diffusion to domestic industries and eventually for sustainable development. Against this backdrop, this study utilizes firm-level panel datasets from Ethiopia to address the following couple of research questions. The first question is: are there any productivity differences between the establishment of Chinese-affiliated and domestic firms in the manufacturing industry in Ethiopia? The second is, does the presence of Chinese-affiliated firms provide productivity spillovers for domestic firms in the same industry level for socio-economic development? The investigation was carried out using 2554 manufacturing firm census data, from which 15.04% were Chinese firms operating in Ethiopia. We used the ordinary least squares (OLS) and generalized-method-of-moments (GMM) two-step approaches for estimations. Our findings revealed that, generally, Chinese firms were more productive than local firms and their presence can bring positive potential productivity spillover effects for domestic firms. Specifically, we found that local firms have gained significant positive spillovers when they had a high absorptive capacity, whereas low-absorptive capacity firms suffered negative spillovers. We also found that non-exporting domestic firms experience significant positive spillovers from the presence of Chinese firms.
Evaluating Regional Eco-Green Cooperative Development Based on a Heterogeneous Multi-Criteria Decision-Making Model: Example of the Yangtze River Delta Region
Authors: Yang Yunpeng , Liu Zhiqiang , Chen Hongmin , Wang Yaqiong , Yuan Guanghui
Published: April 2020

The coordinated development evaluation problem of a regional eco-green cooperative can be formulated as a heterogeneous multi-criteria decision-making (HMCDM) problem. Evaluation information can contain qualitative information and quantitative information, but it cannot determine the weight of the interdependence criteria subjectively. Firstly, this paper constructs an evaluation index system for regional ecological green coordinated development. The system includes four dimensions of coordinated development: the regional ecological environment, economic environment, social environment and policy environment, including 20 indicators with heterogeneous and multi-attribute characteristics. Secondly, we construct a heterogeneous multi-attribute decision-making model by calculating the relative closeness, and use the closeness to construct the value function to determine the weight index of each attribute. Finally, we make an empirical study on the performance evaluation of regional ecological green coordinated development of 27 cities in the central area of the Yangtze River Delta in China. The results show that the main driving force for the improvement of the level of regional ecological green coordinated development is the high-quality economic development, and the main obstacles to the degree of coordinated development of regional ecological green development are high energy consumption, high pollution and high emissions in industrial development; and a result found by sorting the degree of the regional ecological green coordinated development in the Yangtze River Delta city group. The heterogeneous multi-attribute decision model we proposed can effectively solve the weights of the ecological green collaborative development indicators, and the method has feasibility and effectiveness.
Dynamic Fuzzy Adjustment Algorithm for Web Information Acquisition and Data Transmission
Authors: Peng Hao , Yang Shun , Liu Qiong , Peng Qiong , Li Qiao
Published: April 2020

In order to improve the transmission dynamic fuzzy adjustment ability of web information acquisition data, a dynamic fuzzy adjustment method of web information acquisition data transmission based on auto correlation feature matching is proposed. This paper constructs the key transfer protocol of the dynamic fuzzy adjustment of web information acquisition data transmission, uses a chaotic sequence structure reconstruction design method to carry out vector quantization and coding processing in the process of the dynamic fuzzy adjustment of web information acquisition data transmission, extracts nonlinear associated feature quantities of web information acquisition data, adopts a statistical feature detection method to select features in dynamic fuzzy adjustment process of web information acquisition data transmission, constructs a feature selection model of the dynamic fuzzy adjustment of web information acquisition data transmission, dynamically adjusts the fuzzy data with a fuzzy information clustering analysis method, and dynamically adjusts the fuzzy data transmission through fuzzy design and fuzzy encryption. The simulation results show that the dynamic fuzzy adjustment of web information acquisition data transmission when using this method is better, and the accurate transmission ability is stronger.
Rightward Shift of Two-Channel NIRS-Defined Prefrontal Cortex Activity during Mental Arithmetic Tasks with Increasing Levels of State Anxiety
Authors: Horiuchi-Hirose Miwa , Sawada Kazuhiko
Published: April 2020

This study was aimed at clarifying the effect of different levels of state anxiety caused by mental arithmetic tasks on the anxiety- and/or task performance-related activation of the frontopolar prefrontal cortex (PFC). Twenty-six healthy male subjects performed two sets of mental arithmetic tasks, which consisted of two difficulty levels. Anxiety levels were evaluated subjectively by the State–Trait Anxiety Inventory-Form JYZ (STAI). Near-infrared spectroscopy (NIRS) measurements revealed greater levels of oxyhemoglobin in the frontopolar PFC during experimental tasks. When the subjects were divided into three anxiety groups based on STAI scores, arithmetic task performance was reduced in the moderate and high state anxiety groups compared the low state anxiety group during the experimental task, but not in the control task. Increased frontopolar PFC activity during the experimental task was observed on either side in the moderate anxiety group. The laterality of frontopolar PFC activity in moderate and high state anxiety groups shifted from left to right dominance, independent of task difficulty. Our findings suggested that reduced task performance increased the difficulty of the arithmetic tasks and was involved in the state anxiety-associated rightward lateralization of the frontopolar PFC.
Multiple Aerodynamic Coefficient Prediction of Airfoils Using a Convolutional Neural Network
Authors: Chen Hai , He Lei , Qian Weiqi , Wang Song
Published: April 2020

Both symmetric and asymmetric airfoils are widely used in aircraft design and manufacture, and they have different aerodynamic characteristics. In order to improve flight performance and ensure flight safety, the aerodynamic coefficients of these airfoils must be obtained. Various methods are used to generate aerodynamic coefficients. The prediction model is a promising method that can effectively reduce cost and time. In this paper, a graphical prediction method for multiple aerodynamic coefficients of airfoils based on a convolutional neural network (CNN) is proposed. First, a transformed airfoil image (TAI) was constructed by using the flow-condition convolution with the airfoil image. Next, TAI was combined with the original airfoil image to form a composite airfoil image (CAI) that is used as the input of the CNN prediction model. Then, the structure and parameters of the prediction model were designed according to CAI features. Finally, a sample set that was generated on the basis of the deformation of symmetrical airfoil NACA 0012 was used to train and test the prediction model. Simulation results showed that the proposed method based on CNN could simultaneously predict the pitch-moment, drag, and lift coefficients, and prediction accuracy was high.
A Symmetric Controllable Hyperchaotic Hidden Attractor
Authors: Zhang Xin , Li Chunbiao , Lei Tengfei , Liu Zuohua , Tao Changyuan
Published: April 2020

By introducing a simple feedback, a hyperchaotic hidden attractor is found in the newly proposed Lorenz-like chaotic system. Some variables of the equilibria-free system can be controlled in amplitude and offset by an independent knob. A circuit experiment based on Multisim is consistent with the theoretic analysis and numerical simulation.
Dynamic Evolution of Safety Regulation of the Ridesharing Industry under Social Media Participation
Authors: Sun Qipeng , Li Tingzhen , Ma Fei , Guo Xiaozhuang , Wang Sijie
Published: April 2020

The emergence of ridesharing has spread against the background of the sharing economy. There have been a lot of controversies since the emergence of ridesharing, particularly regarding regulatory issues. The safety regulation of the ridesharing industry involves many parties, including governments, platform companies, and society at large. Currently, because of the influence of information asymmetry, it increases the uncertainty of governments’ regulation effect and the difficulty of making regulation measures. Meanwhile, social media, one of the most important forces of social regulation, has not paid enough attention to playing an appropriate role in the safety regulation of the ridesharing industry. Therefore, this study constructs an evolutionary game model between governments and platform companies that concerns the safety regulations of ridesharing passengers under social media participation. The influence path of social media is explored by model solution and numerical simulation. Our results indicate that social media participation has a positive impact on this safety regulation. Specifically, social media participation could reduce governments’ regulatory costs and encourage it to strictly regulate. The exposure of social media could bring losses to platform companies involved and promote platform companies’ investments in improving passengers’ safety. This study provides a decision basis for governments to introduce social media in the safety regulation of the ridesharing industry.
A Parameterized Intuitionistic Type-2 Fuzzy Inference System with Particle Swarm Optimization
Authors: Yu Chun-Min , Lin Kuo-Ping , Liu Gia-Shie , Chang Chia-Hao
Published: April 2020

The aim of this study was to develop a novel intuitionistic Type-2 fuzzy inference system (IT-2 FIS) which adopts a parameterized Yager-generating function and particle swarm optimization (PSO). In IT-2 FIS, the intuitionistic Type-2 is set as a fuzzy symmetrical triangular number in which the hesitation degree adopts the Yager-generating function, and the parameters of the proposed IT-2 FIS adopting the PSO are tuned. The intuitionistic and Type-2 fuzzy sets have been proven to be the most effective for handling more uncertainty. Therefore, this study proposes an intuitionistic Type-2 set with a Yager-generating function to enhance the conventional fuzzy inference system. Moreover, PSO can improve the fuzzy inference system by searching for the optimal parameters of IT-2 FIS. In this study, linguistic variables were represented by triangular fuzzy numbers (TFS). Two numerical examples were examined: capacity-planning and medical diagnosis problems. An approaching capacity-loadings example was used to verify that the proposed IT-2 FIS could effectively estimate the results of the capacity loadings. In the medical diagnosis problem, IT-2 FIS could obtain a higher correct rate by revealing experts’ knowledge. In both examples, the proposed IT-2 FIS provided more objective estimated values than traditional fuzzy inference systems (FIS) and Type-2 FIS.
New Generalized Hermite-Hadamard Inequality and Related Integral Inequalities Involving Katugampola Type Fractional Integrals
Authors: Almutairi Ohud , Kılıçman Adem
Published: April 2020

In this paper, a new identity for the generalized fractional integral is defined. Using this identity we studied a new integral inequality for functions whose first derivatives in absolute value are convex. The new generalized Hermite-Hadamard inequality for generalized convex function on fractal sets involving Katugampola type fractional integral is established. This fractional integral generalizes Riemann-Liouville and Hadamard’s integral, which possess a symmetric property. We derive trapezoid and mid-point type inequalities connected to this generalized Hermite-Hadamard inequality.
Residual Series Representation Algorithm for Solving Fuzzy Duffing Oscillator Equations
Authors: Alshammari Mohammad , Al-Smadi Mohammed , Arqub Omar Abu , Hashim Ishak , Alias Mohd Almie
Published: April 2020

The mathematical structure of some natural phenomena of nonlinear physical and engineering systems can be described by a combination of fuzzy differential equations that often behave in a way that cannot be fully understood. In this work, an accurate numeric-analytic algorithm is proposed, based upon the use of the residual power series, to investigate the fuzzy approximate solution for a nonlinear fuzzy Duffing oscillator, along with suitable uncertain guesses under strongly generalized differentiability. The proposed approach optimizes the approximate solution by minimizing a residual function to generate r-level representation with a rapidly convergent series solution. The influence, capacity, and feasibility of the method are verified by testing some applications. Level effects of the parameter r are given graphically and quantitatively, showing good agreement between the fuzzy approximate solutions of upper and lower bounds, that together form an almost symmetric triangular structure, that can be determined by central symmetry at r = 1 in a convex region. At this point, the fuzzy number is a convex fuzzy subset of the real line, with a normalized membership function. If this membership function is symmetric, the triangular fuzzy number is called the symmetric triangular fuzzy number. Symmetrical fuzzy estimates of solutions curves indicate a sense of harmony and compatibility around the parameter r = 1. The results are compared numerically with the crisp solutions and those obtained by other existing methods, which illustrate that the suggested method is a convenient and remarkably powerful tool in solving numerous issues arising in physics and engineering.