bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Choice of the Third-Frequency Galileo Signals in Accelerating PPP Ambiguity Resolution in Case of Receiver Antenna Phase Center Errors
Authors: Xin Shaoming , Geng Jianghui , Guo Jiang , Meng Xiaolin
Published: April 2020

Rapid precise point positioning ambiguity resolution (PPP-AR) is of great importance to improving precise positioning efficiency. There is an expectation that Galileo multi-frequency (three or more frequencies) data processing will offer a promising way to accelerate PPP-AR. However, the performance of different combination observables out of raw Galileo multi-frequency data is still unclear, and the adverse impacts of missing receiver antenna phase center corrections have not been quantified in detail. We therefore studied uncombined Galileo PPP-AR by contrasting three typical triple-frequency combinations, which are E1/E5a/E5b, E1/E5a/E6, and E1/E5/E6 signals, using 30 days of data from 15 stations across Australia. We carried out triple-frequency PPP-AR by separately applying the official GPS receiver antenna phase centers, as currently employed in most relevant literatures, as well as the pilot Galileo receiver antenna phase centers preliminarily measured by the International GNSS Service. We found that, compared to dual-frequency (E1/E5a) PPP-AR, triple-frequency PPP-AR based on E1/E5a/E5b signals shortened the convergence time by only 7.6%, while those based on E1/E5a/E6 and E1/E5/E6 increased unexpectedly the convergence time by 17.6% and 12.7%, respectively, if the GPS receiver antenna corrections were presumed for Galileo signals. However, after using the pilot Galileo phase center corrections, triple-frequency PPP-AR based on E1/E5a/E5b, E1/E5a/E6, and E1/E5/E6 signals could speed up the convergence on average by about 16.2%, 30.3%, and 17.7%, respectively. Therefore, we demonstrate the critical impact of correct Galileo receiver antenna phase centers on multi-frequency PPP-AR convergences. Moreover, the triple-frequency signal combination E1/E5a/E6 is advantageous over others in achieving rapid triple-frequency Galileo PPP-AR.
Retrieval of Aerodynamic Parameters in Rubber Tree Forests Based on the Computer Simulation Technique and Terrestrial Laser Scanning Data
Authors: Huang Zhixian , Huang Xiao , Fan Jiangchuan , Eichhorn Markus , An Feng , Chen Bangqian , Cao Lin , Zhu Zhengli , Yun Ting
Published: April 2020

Rubber trees along the southeast coast of China always suffer severe damage from hurricanes. Quantitative assessments of the capacity for wind resistance of various rubber tree clones are currently lacking. We focus on a vulnerability assessment of rubber trees of different clones under wind disturbance impacts by employing multidisciplinary approaches incorporating scanned points, aerodynamics, machine learning and computer graphics. Point cloud data from two typical rubber trees belonging to different clones (PR107 and CATAS 7-20-59) were collected using terrestrial laser scanning, and a connection chain of tree skeletons was constructed using a clustering algorithm of machine learning. The concept of foliage clumps based on the trunk and first-order branches was first proposed to optimize rubber tree plot 3D modelling for simulating the wind field and assessing the wind-related parameters. The results from the obtained phenotypic traits show that the variable leaf area index and included angle between the branches and trunk result in variations in the topological structure and gap fraction of tree crowns, respectively, which are the major influencing factors relevant to the rubber tree’s capacity to resist hurricane strikes. The aerodynamics analysis showed that the maximum dynamic pressure, wind velocity and turbulent intensity of the wind-related parameters in rubber tree plots of clone PR107 (300 Pa, 30 m/s and 15%) are larger than that in rubber tree plots of clone CATAS-7-20-59 (120 Pa, 18 m/s and 5%), which results in a higher probability of local strong cyclone occurrence and a higher vulnerability to hurricane damage.
Mapping of Maximum and Minimum Inundation Extents in the Amazon Basin 2014–2017 with ALOS-2 PALSAR-2 ScanSAR Time-Series Data
Authors: Rosenqvist Jessica , Rosenqvist Ake , Jensen Katherine , McDonald Kyle
Published: April 2020

Seasonal inundation is an important effect that governs the distribution of ecosystems in the tropics. In the Amazon Basin, the seasonal flood pulse causes a difference in high and low water levels that can exceed 15 m. The associated flood duration and extent play an important role in land-atmosphere carbon exchange and affect the ecosystem’s carbon pool that originates from organic matter transported from upland and flooded forests. Studies of wetlands inundation across the Amazon Basin have utilized dual season mosaics from JERS-1 and wide-swath ScanSAR data from ALOS PALSAR to characterize inundation across the basin. This study builds upon past efforts with JERS-1 and ALOS PALSAR and uses ALOS-2 PALSAR-2 ScanSAR data to generate annual maximum and minimum inundation extent maps over the full Amazon Basin for the period spanning November 2014–October 2017. The study uses decision tree classification to create a maximum and a minimum inundation extent map for each year over this time period. The results show that a generalized algorithm that fits the entire basin has an 86% overall accuracy compared with a classification made for a local region from the same PALSAR-2 datasets. Comparisons with previous full-basin inundation maps by other L-band radars shows similar results for inundated areas during maximum inundation. The maps derived previously from JERS-1 and ALOS PALSAR show 7.3% and 6.9% inundated vegetation, respectively, and this study using PALSAR-2 shows values ranging between 5.5% and 7.0% across the three study years. Comparisons between the stage data across the basin and acquisition dates/periods for JERS-1 and PALSAR-2 show that the sensors capture the nature of the maximum and minimum flooding across the basins but have not successfully captured the exact maximum and minimum flood levels that have been recorded in the stage data. The inundation maps are publicly available under a Creative Commons (CC BY 4.0) licensefrom the Alaska Satellite Facility.
Earth Observation Contribution to Cultural Heritage Disaster Risk Management: Case Study of Eastern Mediterranean Open Air Archaeological Monuments and Sites
Authors: Agapiou Athos , Lysandrou Vasiliki , Hadjimitsis Diofantos G.
Published: April 2020

Disaster risk management (DRM) for cultural heritage is a complex task that requires multidisciplinary cooperation. This short communication underlines the critical role of satellite remote sensing (also known as earth observation) in DRM in dealing with various hazards for cultural heritage sites and monuments. Here, satellite observation potential is linked with the different methodological steps of the DRM cycle. This is achieved through a short presentation of recent paradigms retrieved from research studies and the Scopus scientific repository. The communication focuses on the Eastern Mediterranean region, an area with an indisputable wealth of archaeological sites. Regarding the cultural heritage type, this article considers relevant satellite observation studies implemented in open-air archaeological monuments and sites. The necessity of this communication article emerged while trying to bring together earth observation means, cultural heritage needs, and DRM procedures.
Revealing the Fingerprint of Climate Change in Interannual NDVI Variability among Biomes in Inner Mongolia, China
Authors: Guo Linghui , Zuo Liyuan , Gao Jiangbo , Jiang Yuan , Zhang Yongling , Ma Shouchen , Zou Youfeng , Wu Shaohong
Published: April 2020

An understanding of the response of interannual vegetation variations to climate change is critical for the future projection of ecosystem processes and developing effective coping strategies. In this study, the spatial pattern of interannual variability in the growing season normalized difference vegetation index (NDVI) for different biomes and its relationships with climate variables were investigated in Inner Mongolia during 1982–2015 by jointly using linear regression, geographical detector, and geographically weighted regression methodologies. The result showed that the greatest variability of the growing season NDVI occurred in typical steppe and desert steppe, with forest and desert most stable. The interannual variability of NDVI differed monthly among biomes, showing a time gradient of the largest variation from northeast to southwest. NDVI interannual variability was significantly related to that of the corresponding temperature and precipitation for each biome, characterized by an obvious spatial heterogeneity and time lag effect marked in the later period of the growing season. Additionally, the large slope of NDVI variation to temperature for desert implied that desert tended to amplify temperature variations, whereas other biomes displayed a capacity to buffer climate fluctuations. These findings highlight the relationships between vegetation variability and climate variability, which could be used to support the adaptive management of vegetation resources in the context of climate change.
Combining Fractional Cover Images with One-Class Classifiers Enables Near Real-Time Monitoring of Fallows in the Northern Grains Region of Australia
Authors: Zhao Liya , Waldner François , Scarth Peter , Mack Benjamin , Hochman Zvi
Published: April 2020

Fallows are widespread in dryland cropping systems. However, timely information about their spatial extent and location remains scarce. To overcome this lack of information, we propose to classify fractional cover data from Sentinel-2 with biased support vector machines. Fractional cover images describe the land surface in intuitive, biophysical terms, which reduces the spectral variability within the fallow class. Biased support vector machines are a type of one-class classifiers that require labelled data for the class of interest and unlabelled data for the other classes. They allow us to extrapolate in-situ observations collected during flowering to the rest of the growing season to generate large training data sets, thereby reducing the data collection requirements. We tested this approach to monitor fallows in the northern grains region of Australia and showed that the seasonal fallow extent can be mapped with >92% accuracy both during the summer and winter seasons. The summer fallow extent can be accurately mapped as early as mid-December (1–4 months before harvest). The winter fallow extent can be accurately mapped from mid-August (2–4 months before harvest). Our method also detected emergence dates successfully, indicating the near real-time accuracy of our method. We estimated that the extent of fallow fields across the northern grains region of Australia ranged between 50% in winter 2017 and 85% in winter 2019. Our method is scalable, sensor independent and economical to run. As such, it lays the foundations for reconstructing and monitoring the cropping dynamics in Australia.
SI-Traceability and Measurement Uncertainty of the Atmospheric Infrared Sounder Version 5 Level 1B Radiances
Authors: Pagano Thomas S. , Aumann Hartmut H. , Broberg Steven E. , Cañas Chase , Manning Evan M. , Overoye Kenneth O. , Wilson Robert C.
Published: April 2020

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on 4 May 2002. The AIRS is designed to measure atmospheric temperature and water vapor profiles and has demonstrated exceptional radiometric and spectral accuracy and stability in orbit. The International System of Units (SI)-traceability of the derived radiances is achieved by transferring the calibration from the Large Area Blackbody (LABB) with SI traceable temperature sensors, to the On-Board Calibrator (OBC) blackbody during preflight testing. The AIRS views the OBC blackbody and four full aperture space views every scan. A recent analysis of pre-flight and on-board data has improved our understanding of the measurement uncertainty of the Version 5 AIRS L1B radiance product. For temperatures greater than 260 K, the measurement uncertainty is better than 250 mK 1-sigma for most channels. SI-traceability and quantification of the radiometric measurement uncertainty is critical to reducing biases in reanalysis products and radiative transfer models (RTMs) that use AIRS data, as well as establishing the suitability of AIRS as a benchmark for radiances established in the early 2000s.
Towards the Concurrent Execution of Multiple Hyperspectral Imaging Applications by Means of Computationally Simple Operations
Authors: Díaz María , Guerra Raúl , Horstrand Pablo , López Sebastián , López José F. , Sarmiento Roberto
Published: April 2020

The on-board processing of remotely sensed hyperspectral images is gaining momentum for applications that demand a quick response as an alternative to conventional approaches where the acquired images are off-line processed once they have been transmitted to the ground segment. However, the adoption of this on-board processing strategy brings further challenges for the remote-sensing research community due to the high data rate of the new-generation hyperspectral sensors and the limited amount of available on-board computational resources. This situation becomes even more stringent when different time-sensitive applications coexist, since different tasks must be sequentially processed onto the same computing device. In this work, we have dealt with this issue through the definition of a set of core operations that extracts spectral features useful for many hyperspectral analysis techniques, such as unmixing, compression and target/anomaly detection. Accordingly, it permits the concurrent execution of such techniques reusing operations and thereby requiring much less computational resources than if they were separately executed. In particular, in this manuscript we have verified the goodness of our proposal for the concurrent execution of both the lossy compression and anomaly detection processes in hyperspectral images. To evaluate the performance, several images taken by an unmanned aerial vehicle have been used. The obtained results clearly support the benefits of our proposal not only in terms of accuracy but also in terms of computational burden, achieving a reduction of roughly 50% fewer operations to be executed. Future research lines are focused on extending this methodology to other fields such as target detection, classification and dimensionality reduction.
The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE
Authors: Zwolak Karolina , Wigley Rochelle , Bohan Aileen , Zarayskaya Yulia , Bazhenova Evgenia , Dorshow Wetherbee , Sumiyoshi Masanao , Sattiabaruth Seeboruth , Roperez Jaya , Proctor Alison , Wallace Craig , Sade Hadar , Ketter Tomer , Simpson Benjamin , Tinmouth Neil , Falconer Robin , Ryzhov Ivan , Elsaied Abou-Mahmoud Mohamed
Published: April 2020

The methods of data collection, processing, and assessment of the quality of the results of a survey conducted at the Southern Ionian Sea off the Messinian Peninsula, Greece are presented. Data were collected by the GEBCO-Nippon Foundation Alumni Team, competing in the Shell Ocean Discovery XPRIZE, during the Final Round of the competition. Data acquisition was conducted by the means of unmanned vehicles only. The mapping system was composed of a single deep water AUV (Autonomous Underwater Vehicle), equipped with a high-resolution synthetic aperture sonar HISAS 1032 and multibeam echosounder EM 2040, partnered with a USV (Unmanned Surface Vessel). The USV provided positioning data as well as mapping the seafloor from the surface, using a hull-mounted multibeam echosounder EM 304. Bathymetry and imagery data were collected for 24 h and then processed for 48 h, with the extensive use of cloud technology and automatic data processing. Finally, all datasets were combined to generate a 5-m resolution bathymetric surface, as an example of the deep-water mapping capabilities of the unmanned vehicles’ cooperation and their sensors’ integration.
Data Fusion of Scanned Black and White Aerial Photographs with Multispectral Satellite Images
Authors: Kaimaris Dimitris , Patias Petros , Mallinis Giorgos , Georgiadis Charalampos
Published: April 2020

To date, countless satellite image fusions have been made, mainly with panchromatic spatial resolution to a multispectral image ratio of 1/4, fewer fusions with lower ratios, and relatively recently fusions with much higher spatial resolution ratios have been published. Apart from this, there is a small number of publications studying the fusion of aerial photographs with satellite images, with the year of image acquisition varying and the dates of acquisition not mentioned. In addition, in these publications, either no quantitative controls are performed on the composite images produced, or the aerial photographs are recent and colorful and only the RGB bands of the satellite images are used for data fusion purposes. The objective of this paper is the study of the addition of multispectral information from satellite images to black and white aerial photographs of the 80s decade (1980–1990) with small difference (just a few days) in their image acquisition date, the same year and season. Quantitative tests are performed in two case studies and the results are encouraging, as the accuracy of the classification of the features and objects of the Earth’s surface is improved and the automatic digital extraction of their form and shape from the archived aerial photographs is now allowed. This opens up a new field of use for the black and white aerial photographs and archived multispectral satellite images of the same period in a variety of applications, such as the temporal changes of cities, forests and archaeological sites.
Some Voices from Italian Youth on Well-Being: How to Cope with Job Insecurity?
Authors: Musumeci Rosy , Ghislieri Chiara
Published: April 2020

’Insecure’ jobs and alternating between periods of unemployment and periods of employment under fixed-term contracts are increasingly widespread among the youth in Europe. This phenomenon is an important risk factor for young people’s well-being. Despite the growing number of studies, some issues have still not been adequately addressed. Compared to the high number of quantitative studies, the number of qualitative researches is limited: in fact, few studies have tackled this topic from a qualitative standpoint, highlighting the dynamics and the subjective processes which operate in this relationship and considering the different functions that work can have for the individual. Another aspect that has not been adequately dealt with is represented by the coping strategies that young people put in place to deal with job insecurity, and which have consequences on their well-being. The present article on the Italian case is intended to give a contribution in these directions. In particular, it analyses the way in which a group of 40 unemployed or temporarily employed young people, in-depth interviewed, subjectively describe the relationship between job insecurity and well-being, and reflects on coping strategies to face job insecurity and related perceived consequences. In doing this, the authors consider the role of individual factors, as well as of meso and macro ones, given that—for example—the national contexts have a role in influencing the way in which job insecurity is perceived and managed by individuals. The results highlight the complexity of this relationship, in which the intertwining of factors at different levels plays a very important role in determining the coping strategies and the overall well-being of people: individually, like the functions and the subjective meanings of work for the youth, but also in meso and macro terms, such as the familial support and relationships, and the institutional and public resources available.
Determinants of Guest Experience in Airbnb: A Topic Modeling Approach Using LDA
Authors: Sutherland Ian , Kiatkawsin Kiattipoom
Published: April 2020

This study inductively analyzes the topics of interest that drive customer experience and satisfaction within the sharing economy of the accommodation sector. Using a dataset of 1,086,800 Airbnb reviews across New York City, the text is preprocessed and latent Dirichlet allocation is utilized in order to extract 43 topics of interest from the user-generated content. The topics fall into one of several categories, including the general evaluation of guests, centralized or decentralized location attributes of the accommodation, tangible and intangible characteristics of the listed units, management of the listing or unit, and service quality of the host. The deeper complex relationships between topics are explored in detail using hierarchical Ward Clustering.
Environmental and Socioeconomic Impacts of Urban Waste Recycling as Part of Circular Economy. The Case of Cuenca (Ecuador)
Authors: Burneo Damián , Cansino José M. , Yñiguez Rocio
Published: April 2020

Urban mining by recyclers represents a positive environmental impact as well as being part of the waste management chain. This paper analyzes the contribution of waste pickers in the city of Cuenca in Ecuador and the conditions of their activity. This research has a two-fold objective. First, it calculates the reduction of greenhouse gas emissions resulting from the substitution of virgin raw material in the production process by using recycled urban waste. The second objective is to conduct a socioeconomic analysis of the workers involved in the urban waste sector. Cuenca (Ecuador) is the main city used for this case study, thanks to the accessibility of a rich database built from the survey conducted by the NGO Alliance for Development. The information contained in this survey facilitates the identification of potential consumers of the waste industry. This study uses Clean Development Mechanism methodology. Finally, this work proposes a theoretical model for solid waste management, applied to the city, following the principles of the circular economy.
Field Performance Evaluation and Finite Element Simulation of Cotton Stalk Puller-Shredder: A Sustainable Mechanical Solution to Control Pink Bollworm (Pectinophora Gossypiella)
Authors: Ahmad Fiaz , Jamil Muhammad Tahir , Akhtar Khan Alamgir , Mehmood-Khan Zahid , Qiu Baijing , Ma Jing , Chandio Farman Ali
Published: April 2020

The pink bollworm is one of the most dangerous pests of cotton crops. In order to control it, a number of methods, including physical, chemical, and biological control, have been used. Cotton crop is under threat by various pests, but pink bollworm is its worst enemy, as it not only reduces yield, but also affects the cotton fiber quality. Cotton bolls are the oviposition sites of this pest. The application of chemicals does not affect pink bollworms’ efficiently due to their hidden position in the cotton bolls. Therefore, their accommodation has to be destroyed. A cotton stalk puller shredder (designed and developed by Agriculture Mechanization Research Institute, Multan (AMRI) and Agritech Industry Multan) was tested to determine its field performance. The performance evaluation of the machine was conducted in a goat-grazed and an ungrazed field. The machine was tested at three engine speeds and three levels of forward ground speed. A finite element analysis of parts of the cotton stalk puller-shredder was performed for the purpose of improving the machine’s efficiency. A static structure analysis of the soil cutting blade at four attachment angles (30°, 45°, 60°, and 75°) showed that a maximum equivalent stress of 584 MPa at 75° and a maximum total deformation of 0.75 mm and maximum directional deformation of 0.74 mm were observed with a blade attachment angle of 75°.
Terrorist Threat Mitigation Strategies for the Railways
Authors: Luxton Abigail , Marinov Marin
Published: April 2020

Terrorism is an ever-present threat that is becoming more prevalent in today’s society. The railway has always been a favourable target for terrorists due to the high volume of people that utilise it, as well as the vital services it provides to the nation. The railway is expanding and this will likely result in it becoming increasingly vulnerable to attack, unless new mitigation solutions are devised. In this paper risk assessment analyses by a software package conducted on different sections of the railway station provided insight into the present vulnerabilities. Mitigation solutions were devised to abolish these weaknesses in the system, to avoid terrorist exploitation. They were then evaluated to establish a workable solution: a modified version of the Thales Smart Corridor. This workable solution should be implemented across the nation to ensure passenger and rail infrastructure protection.
Environmental and Economic Evaluation of Small-Scale Bridge Repair Using Cross-Laminated Timber Floor Slabs
Authors: Iwase Tetsuya , Sasaki Takanobu , Araki Shogo , Huzita Tomohumi , Kayo Chihiro
Published: April 2020

Cross-laminated timber (CLT) has gained popularity worldwide in recent years, and its use in buildings and civil engineering structures has attracted attention in Japan. In this study, the life-cycle greenhouse gas (GHG) balance and costs associated with CLT floor slabs were evaluated with respect to small-scale bridge repair as the first instance of the use of CLT in civil engineering projects in Japan. Additionally, waterproofing treatment was applied to CLT slabs, and the potential GHG and cost reduction of CLT in comparison with reinforced concrete (RC) slabs were examined. GHG emissions were the smallest for non-waterproofed CLT slabs and the greatest for RC slabs. When replacing RC slabs with CLT slabs without waterproofing, fossil-derived GHG emissions can be reduced by 73 kg-CO2eq/m2 per slab, and fossil/wood-derived GHG emissions can be reduced by 67 kg-CO2eq/m2; however, the use of disposed CLT as fuel is essential. Moreover, a reduction in GHG emissions can be expected if RC slabs are replaced with CLT slabs that are waterproofed only once every 20 years. Further, the cost associated with RC slabs is 20% of that attributable to CLT slabs. Hence, measures need to be taken to reduce the cost of CLT and waterproofing materials.
Sustainable Causal Interpretation with Board Characteristics: Caveat Emptor
Authors: Kim Jong-Min , Jun Chulhee , Han Hope H.
Published: April 2020

The study of a causal interpretation of board and firm characteristics, that is, a hidden dependence relationship on the causal inference among board and firm characteristics, is an important but unaddressed issue in the corporate governance literature. Using diverse advanced statistical methods and focusing on Tobin’s Q, we find that (i) not all board variables previously found to be significant are “robust” to latent variable data analysis, and (ii) those variables that are consistently significant differ markedly in latent structural equation analysis. Our analyses provide researchers interested in board issues with an important caveat: Focusing on the dependence structure of available board variables affected by latent factors may introduce a new horizon in corporate finance.
Evolution and Management of Illegal Settlements in Mid-Sized Towns. The Case of Sierra de Santa Bárbara (Plasencia, Spain)
Authors: Jiménez Barrado Víctor
Published: April 2020

The illegal urbanization of rural areas near cities has unveiled failures in urban management. In many cases, urban policies have ignored this fact until the spaces have consolidated. This is the example of the Sierra de Santa Bárbara (Plasencia, Spain), where legalization becomes one of the most feasible solutions. The present work analyses its residential evolution during the last four decades through historical orthophotos review. Along with this, it evaluates public–private conflicts (homeowners vs municipal government) using regional newspaper archives. The results indicate that the strategy of ignoring illegal development increases these problems, leading to legalization as the only possible urban policy. In conclusion, the administration’s response is delayed and forced by critical consequences, which prevents learning in urban policies and new solutions that join legality and sustainability.
Factors and Paths of Transformation and Upgradation of Chemical Industry in Shandong, China
Authors: Han Huijian , Yang Ye , Zhang Rui , Brekhna Brekhna
Published: April 2020

In the context of the Internet, there is a historical fusion between the new round of scientific and technological revolution and industrial transformation and the accelerated transformation of economic development methods. The task of the Shandong chemical industry’s transformation and upgradation is arduous and urgent. In this context, this article studies the influencing factors and development paths of the transformation and upgradation of the Shandong chemical industry. It provides theoretical guidance for high-quality and sustainable development of the Shandong chemical industry. First, this paper uses the fuzzy cognitive map tool to learn the historical laws of the transformation and upgradation of the Shandong chemical industry. It then determines the path of chemical industry transformation and upgradation, according to the interactions and weights between the learned indicators. By adjusting the influence coefficient between the indicators on each path, the degree of change in the influence of the indicator on the target value is analyzed. The critical path and the key indicators on the path according to the degree of impact are determined. Finally, the key path selected in this article is: return on investment (C8) → unit production value environmental consumption (C9) → number of R&D personnel (C4) → R&D expenditure internal expenditure (C6) → industrial output (C1) → energy consumption coefficient (C3). The key indicator on this path is R&D expenditure internal expenditure. According to the results, the development suggestion for the transformation and upgradation of the chemical industry in Shandong is to take the path of green development through technological innovation.
Proposal of a Holistic Framework to Support Sustainability of New Product Innovation Processes
Authors: Dias Ana S. M. E. , Abreu António , Navas Helena V. G. , Santos Ricardo
Published: April 2020

The survival of companies in globalized and highly competitive markets, heavily depends on their ability to innovate through the creation of new products and/or services, supported by sustainable processes to prevent business failure. There are many factors regarding the interface company/stakeholders/market at all hierarchical levels, which have a major contribution to sustain innovation in processes regarding the creation of new products and services. A holistic approach of all these factors, as a whole, has not been a subject of scientific research conducting to the necessity of creating a proposal of a framework that can be integrated and systemic. Thus, this paper aims to propose a functional holistic model, which integrates the strategic, organizational and operational levels regarding market business and company interaction, as well as the set of factors to take into account to guarantee assurance that innovative processes are sustained, when new products and/or services are created or improved. Conducted through an investigation of the state of the art, by literature review, a comprehensive and integrated conceptual model was built in a deductive-inductive way. Then, the conceptual model was validated through four case studies. Finally, it was found that the conceptual framework became functional, because its applicability has been successfully tested in a business environment. As a result, the tool developed here, can be useful to measure and evaluate projects dedicated to companies that innovate in a sustainable way.
Development and Application of Precast Concrete Double Wall System to Improve Productivity of Retaining Wall Construction
Authors: Kim Seungho , Lee Dong-Eun , Kim Yonggu , Kim Sangyong
Published: April 2020

The construction of most apartment underground parking lots utilizes reinforced concrete (RC) structures composed mainly of rebar work and formwork. RC structures lower construction efficiency and significantly delay the construction because they require a large number of temporary materials and wooden formwork. In this study, a precast concrete double wall (PCDW) system was developed to address the existing problems of RC structures and to improve the productivity of retaining wall construction. PCDW is a precast concrete (PC) wall in which two thin concrete panels are connected parallel to each other with truss-shaped reinforcement between them. PCDW can contribute to securing integrity, reducing the delay in construction, and improving quality. An overall process for the member design and construction stage of the PCDW system was proposed, and its improvement effects were examined regarding various aspects in comparison to the RC method.
Direct Power Compensation in AC Distribution Networks with SCES Systems via PI-PBC Approach
Authors: Gil-González Walter , Martin Serra Federico , Montoya Oscar Danilo , Ramírez Carlos Alberto , Orozco-Henao César
Published: April 2020

Here, we explore the possibility of employing proportional-integral passivity-based control (PI-PBC) to support active and reactive power in alternating current (AC) distribution networks by using a supercapacitor energy storage system. A direct power control approach is proposed by taking advantage of the Park’s reference frame transform direct and quadrature currents ( i d and i q ) into active and reactive powers (p and q). Based on the open-loop Hamiltonian model of the system, we propose a closed-loop PI-PBC controller that takes advantage of Lyapunov’s stability to design a global tracking controller. Numerical simulations in MATLAB/Simulink demonstrate the efficiency and robustness of the proposed controller, especially for parametric uncertainties.
An Imbalanced Data Handling Framework for Industrial Big Data Using a Gaussian Process Regression-Based Generative Adversarial Network
Authors: Oh Eunseo , Lee Hyunsoo
Published: April 2020

The developments in the fields of industrial Internet of Things (IIoT) and big data technologies have made it possible to collect a lot of meaningful industrial process and quality-based data. The gathered data are analyzed using contemporary statistical methods and machine learning techniques. Then, the extracted knowledge can be used for predictive maintenance or prognostic health management. However, it is difficult to gather complete data due to several issues in IIoT, such as devices breaking down, running out of battery, or undergoing scheduled maintenance. Data with missing values are often ignored, as they may contain insufficient information from which to draw conclusions. In order to overcome these issues, we propose a novel, effective missing data handling mechanism for the concepts of symmetry principles. While other existing methods only attempt to estimate missing parts, the proposed method generates a whole set of data set using Gaussian process regression and a generative adversarial network. In order to prove the effectiveness of the proposed framework, we examine a real-world, industrial case involving an air pressure system (APS), where we use the proposed method to make quality predictions and compare the results with existing state-of-the-art estimation methods.
Symmetry for Multimedia-Aided Art Teaching Based on the Form of Animation Teaching Organization and Social Network
Authors: Xie Zheng
Published: April 2020

Symmetries play a vital role in multimedia-aided art teaching activities. The relevant teaching systems designed with a social network, including the optimized teaching methods, are on the basis of symmetry principles. In order to study art teaching, from the perspective of the teaching organization form, combined with the survey method, multimedia-aided art classroom teaching was explained in detail. Based on the symmetrical thinking in art teaching, the multimedia-aided teaching mode of art classroom was discussed. The reasons for the misunderstanding of multimedia-aided art teaching were analyzed, and the core factors affecting the use of multimedia art teaching were found. In art teaching, more real pictures were shown aided by multimedia; students could experience the beauty of symmetrical things in real life and were guided to find the artistic characteristics of these kinds of graphics, analyze them, and summarize them. The results showed that this method enriched the art multimedia teaching theory and improved the efficiency of art teaching. The blind use of multimedia technology by teachers in art classroom teaching was avoided. Therefore, the method can develop individualized teaching, develop students’ potential, and cultivate innovative consciousness and practical ability.
The bZIP Transcription Factor AflRsmA Regulates Aflatoxin B1 Biosynthesis, Oxidative Stress Response and Sclerotium Formation in Aspergillus flavus
Authors: Wang Xiuna , Zha Wenjie , Liang Linlin , Fasoyin Opemipo Esther , Wu Lihan , Wang Shihua
Published: April 2020

Fungal secondary metabolites play important roles not only in fungal ecology but also in humans living as beneficial medicine or harmful toxins. In filamentous fungi, bZIP-type transcription factors (TFs) are associated with the proteins involved in oxidative stress response and secondary metabolism. In this study, a connection between a bZIP TF and oxidative stress induction of secondary metabolism is uncovered in an opportunistic pathogen Aspergillus flavus, which produces carcinogenic and mutagenic aflatoxins. The bZIP transcription factor AflRsmA was identified by a homology research of A. flavus genome with the bZIP protein RsmA, involved in secondary metabolites production in Aspergillus nidulans. The AflrsmA deletion strain (ΔAflrsmA) displayed less sensitivity to the oxidative reagents tert-Butyl hydroperoxide (tBOOH) in comparison with wild type (WT) and AflrsmA overexpression strain (AflrsmAOE), while AflrsmAOE strain increased sensitivity to the oxidative reagents menadione sodium bisulfite (MSB) compared to WT and ΔAflrsmA strains. Without oxidative treatment, aflatoxin B1 (AFB1) production of ΔAflrsmA strains was consistent with that of WT, but AflrsmAOE strain produced more AFB1 than WT; tBOOH and MSB treatment decreased AFB1 production of ΔAflrsmA compared to WT. Besides, relative to WT, ΔAflrsmA strain decreased sclerotia, while AflrsmAOE strain increased sclerotia. The decrease of AFB1 by ΔAflrsmA but increase of AFB1 by AflrsmAOE was on corn. Our results suggest that AFB1 biosynthesis is regulated by AflRsmA by oxidative stress pathways and provide insights into a possible function of AflRsmA in mediating AFB1 biosynthesis response host defense in pathogen A. flavus.
Molecular Identification and Mycotoxin Production by Alternaria Species Occurring on Durum Wheat, Showing Black Point Symptoms
Authors: Masiello Mario , Somma Stefania , Susca Antonia , Ghionna Veronica , Logrieco Antonio Francesco , Franzoni Matteo , Ravaglia Stefano , Meca Giuseppe , Moretti Antonio
Published: April 2020

Black point is a fungal disease of wheat, mainly associated with mycotoxigenic Alternaria species. Affected wheat kernels are characterized by dark brown discolouration of the embryo region and reduction of grain quality. Potential risk is the possible accumulation of Alternaria mycotoxins, alternariol (AOH), alternariol-monomethyl ether (AME), tenuazonic acid (TA), and altenuene (ALT), provided by haemato-toxic, genotoxic, and mutagenic activities. One hundred and twenty durum wheat samples belonging to 30 different genotypes grown in Bologna and Modena areas, in Italy, showing black point symptoms, were analyzed for Alternaria species and their mycotoxin contamination. Alternariol was selected as an indicator of the capability of the Alternaria species to produce mycotoxin in vivo in field conditions. The data showed that Alternaria species occurred in 118 out of 120 wheat kernels samples, with the incidence of infected kernels ranging between 1% and 26%. Moreover, AOH was detected by using a HPLC with a diode array detector (LC-DAD) in 98 out of 120 samples with values ranging between 24 and 262 µg Kg−1. Ninety-two Alternaria representative strains, previously identified morphologically, were identified at species/section level using gene sequencing, and therefore were analyzed for their mycotoxin profiles. Eighty-four strains, phylogenetically grouped in the Alternaria section, produced AOH, AME, and TA with values up to 8064, 14,341, and 3683 µg g−1, respectively, analyzed by using a LC-DAD. On the other hand, eight Alternaria strains, included in Infectoriae Section, showed a very low or no capability to produce mycotoxins.
Broadly Neutralizing Bovine Antibodies: Highly Effective New Tools against Evasive Pathogens?
Authors: Burke Matthew J. , Stockley Peter G. , Boyes Joan
Published: April 2020

Potent antibody-mediated neutralization is critical for an organism to combat the vast array of pathogens it will face during its lifetime. Due to the potential genetic diversity of some viruses, such as HIV-1 and influenza, standard neutralizing antibodies are often ineffective or easily evaded as their targets are masked or rapidly mutated. This has thwarted efforts to both prevent and treat HIV-1 infections and means that entirely new formulations are required to vaccinate against influenza each year. However, some rare antibodies isolated from infected individuals confer broad and potent neutralization. A subset of these broadly neutralizing antibodies possesses a long complementarity-determining 3 region of the immunoglobulin heavy chain (CDR H3). This feature generates unique antigen binding site configurations that can engage conserved but otherwise inaccessible epitope targets thus neutralizing many viral variants. Remarkably, ultralong CDR H3s are a common feature of the cow antibody repertoire and are encoded by a single variable, diversity, joining (VDJ) recombination that is extensively diversified prior to antigen exposure. Recently, it was shown that cows rapidly generate a broadly neutralizing response upon exposure to HIV-1 and this is primarily mediated by these novel ultralong antibody types. This review summarises the current knowledge of these unusual CDR H3 structures and discusses their known and potential future uses.
HIV-1 Sub-Subtype A6: Settings for Normalised Identification and Molecular Epidemiology in the Southern Federal District, Russia
Authors: Schlösser Madita , Kartashev Vladimir V. , Mikkola Visa H. , Shemshura Andrey , Saukhat Sergey , Kolpakov Dmitriy , Suladze Alexandr , Tverdokhlebova Tatiana , Hutt Katharina , Heger Eva , Knops Elena , Böhm Michael , Di Cristanziano Veronica , Kaiser Rolf , Sönnerborg Anders , Zazzi Maurizio , Bobkova Marina , Sierra Saleta
Published: April 2020

Russia has one of the largest and fastest growing HIV epidemics. However, epidemiological data are scarce. Sub-subtype A6 is most prevalent in Russia but its identification is challenging. We analysed protease/reverse transcriptase-, integrase-sequences, and epidemiological data from 303 patients to develop a methodology for the systematisation of A6 identification and to describe the HIV epidemiology in the Russian Southern Federal District. Drug consumption (32.0%) and heterosexual contact (27.1%) were the major reported transmission risks. This study successfully established the settings for systematic identification of A6 samples. Low frequency of subtype B (3.3%) and large prevalence of sub-subtype A6 (69.6%) and subtype G (23.4%) were detected. Transmitted PI- (8.8%) and NRTI-resistance (6.4%) were detected in therapy-naive patients. In therapy-experienced patients, 17.3% of the isolates showed resistance to PIs, 50.0% to NRTI, 39.2% to NNRTIs, and 9.5% to INSTIs. Multiresistance was identified in 52 isolates, 40 corresponding to two-class resistance and seven to three-class resistance. Two resistance-associated-mutations significantly associated to sub-subtype A6 samples: A62VRT and G190SRT. This study establishes the conditions for a systematic annotation of sub-subtype A6 to normalise epidemiological studies. Accurate knowledge on South Russian epidemiology will allow for the development of efficient regional frameworks for HIV-1 infection management.
Transport of Phage in Melon Plants and Inhibition of Progression of Bacterial Fruit Blotch
Authors: Rahimi-Midani Aryan , Choi Tae-Jin
Published: April 2020

Bacterial fruit blotch (BFB) is an economically important disease in melons and watermelons for which no effective control method is available. Application of phytobacterium-infecting phage has been evaluated as an alternative means of preventing bacterial diseases in plants. Coating of seeds with bacteriophages infecting Acidovorax citrulli, the causal agent of BFB, is effective for controlling the disease, as shown in our previous study. We evaluated the transport of bacteriophage ACPWH from soil to the leaves of melon plants, and we also evaluated its effect on BFB. Leaves of melon plants were spray-inoculated with A. citrulli, and bacteriophage ACPWH was added to soil after symptoms had developed. ACPWH was detected by PCR in foliar tissue 8 h after addition to soil. DAPI-stained ACPWH accumulated at the leaf tip after 24 h. Melon treated with ACPWH showed 27% disease severity, compared to 80% for the non-treated control, indicating that ACPWH can be used to control BFB.
Pantoea agglomerans-Infecting Bacteriophage vB_PagS_AAS21: A Cold-Adapted Virus Representing a Novel Genus within the Family Siphoviridae
Authors: Šimoliūnienė Monika , Truncaitė Lidija , Petrauskaitė Emilija , Zajančkauskaitė Aurelija , Meškys Rolandas , Skapas Martynas , Kaupinis Algirdas , Valius Mindaugas , Šimoliūnas Eugenijus
Published: April 2020

A novel cold-adapted siphovirus, vB_PagS_AAS21 (AAS21), was isolated in Lithuania using Pantoea agglomerans as the host for phage propagation. AAS21 has an isometric head (~85 nm in diameter) and a non-contractile flexible tail (~174 × 10 nm). With a genome size of 116,649 bp, bacteriophage AAS21 is the largest Pantoea-infecting siphovirus sequenced to date. The genome of AAS21 has a G+C content of 39.0% and contains 213 putative protein-encoding genes and 29 genes for tRNAs. A comparative sequence analysis revealed that 89 AAS21 open reading frames (ORFs) code for unique proteins that have no reliable identity to database entries. In total, 63 AAS21 ORFs were functionally annotated, including those coding for the proteins responsible for virion morphogenesis, phage-host interactions, and DNA metabolism. Proteomic analysis led to the experimental identification of 19 virion proteins, including 11 that were predicted by bioinformatics approaches. Based on comparative phylogenetic analysis, AAS21 cannot be assigned to any genus currently recognized by ICTV and may represents a new branch of viruses within the family Siphoviridae.