bluuebunny/crossref_metadata_2025 huggingface dataset:
Extreme Low-Light Image Enhancement for Surveillance Cameras Using Attention U-Net
Authors: Ai Sophy , Kwon Jangwoo
Published: January 2020

Low-light image enhancement is one of the most challenging tasks in computer vision, and it is actively researched and used to solve various problems. Most of the time, image processing achieves significant performance under normal lighting conditions. However, under low-light conditions, an image turns out to be noisy and dark, which makes subsequent computer vision tasks difficult. To make buried details more visible, and reduce blur and noise in a low-light captured image, a low-light image enhancement task is necessary. A lot of research has been applied to many different techniques. However, most of these approaches require much effort or expensive equipment to perform low-light image enhancement. For example, the image has to be captured in a raw camera file in order to be processed, and the addressing method does not perform well under extreme low-light conditions. In this paper, we propose a new convolutional network, Attention U-net (the integration of an attention gate and a U-net network), which is able to work on common file types (.PNG, .JPEG, .JPG, etc.) with primary support from deep learning to solve the problem of surveillance camera security in smart city inducements without requiring the raw image file from the camera, and it can perform under the most extreme low-light conditions.
Monitoring Biochemical and Structural Changes in Human Periodontal Ligaments during Orthodontic Treatment by Means of Micro-Raman Spectroscopy
Authors: Perillo Letizia , d’Apuzzo Fabrizia , Illario Maddalena , Laino Luigi , Di Spigna Gaetano , Lepore Maria , Camerlingo Carlo
Published: January 2020

The aim of the study was to examine the biochemical and structural changes occurring in the periodontal ligament (PDL) during orthodontic-force application using micro-Raman spectroscopy ( μ -RS). Adolescent and young patients who needed orthodontic treatment with first premolar extractions were recruited. Before extractions, orthodontic forces were applied using a closed-coil spring that was positioned between the molar and premolar. Patients were randomly divided into three groups, whose extractions were performed after 2, 7, and 14 days of force application. From the extracted premolars, PDL samples were obtained, and a fixation procedure with paraformaldehyde was adopted. Raman spectra were acquired for each PDL sample in the range of 1000–3200 cm − 1 and the more relevant vibrational modes of proteins (Amide I and Amide III bands) and CH 2 and CH 3 modes were shown. Analysis indicated that the protein structure in the PDL samples after different time points of orthodontic-force application was modified. In addition, changes were observed in the CH 2 and CH 3 high wavenumber region due to local hypoxia and mechanical force transduction. The reported results indicated that μ -RS provides a valuable tool for investigating molecular interchain interactions and conformational modifications in periodontal fibers after orthodontic tooth movement, providing quantitative insight of time occurring for PDL molecular readjustment.
Simulation of the Spectrum Response for the THz Atmosphere Limb Sounder (TALIS)
Authors: Duan Yongqiang , Wang Zhenzhan , Xu Haowen , Wang Wenyu
Published: January 2020

The THz atmospheric limb sounder (TALIS) is a microwave radiometer developed by the National Space Science Center of the Chinese Academy of Sciences for the detection of atmospheric trace gases. The observation range of the instrument mainly focuses on the middle and upper atmosphere (10–100 km above the earth’s surface). The detection targets include the temperature, pressure, and more than 10 kinds of atmospheric components. Its scientific goal is to improve our comprehension of atmospheric chemical composition and dynamics, and to monitor environmental pollution and sources in the atmosphere. The TALIS instrument is composed of an antenna, superheterodyne radiometers, and digital fast Fourier transform (FFT) spectrometers. By measuring the atmospheric thermal radiance in the wide frequency band with 118, 190, 240, and 643 GHz as the center frequency, the required volume mixing ratio (VMR) of atmospheric chemical species can be obtained. This paper introduces the characteristics of the TALIS instrument, and establishes a simulation model for the TALIS spectrometer. Through a joint simulation with an atmosphere radiative transfer simulator (ARTS), the TALIS instrument performance is evaluated from the aspects of calibration, the imbalance of two sidebands, the spectrum resolution, and quantization. The simulation results show that the two-point calibration can well-restore the radiance spectrum of the scene target and remove the influence of the spectral response function (SRF); the double side band (DSB) receiver with a 2 MHz resolution can meet the sensitivity and spectrum resolution requirements. Finally, the sensitivity errors of different quantization bits are given by the simulation and the results show that at 8-bit, the sensitivity and its degradation ratio are 1.251 K and 1.036 at a 2 MHz spectrum resolution and 100 ms integration time, respectively.
Internet of Measurement Things Architecture: Proof of Concept with Scope of Accreditation
Authors: Kaya M. Cagri , Saeedi Nikoo Mahdi , Schwartz Michael L. , Oguztuzun Halit
Published: January 2020

Many industries, such as manufacturing, aviation, and power generation, employ sensitive measurement devices to be calibrated by certified experts. The diversity and sophistication of measurement devices and their calibration needs require networked and automated solutions. Internet of Measurement Things (IoMT) is an architectural framework that is based on the Industrial Internet of Things for the calibration industry. This architecture involves a layered model with a cloud-centric middle layer. In this article, the realization of this conceptual architecture is described. The applicability of the IoMT architecture in the calibration industry is shown through an editor application for Scope of Accreditation. The cloud side of the implementation is deployed to Microsoft Azure. The editor itself is created as a cloud service, and IoT Hub is used to collect data from calibration laboratories. By adapting the IoMT architecture to a commonly used cloud platform, considerable progress is achieved to encompass Metrology data and serve the majority of the stakeholders.
A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System
Authors: Lu Zhenglong , Li Jie , Zhang Xi , Feng Kaiqiang , Wei Xiaokai , Zhang Debiao , Mi Jing , Liu Yang
Published: January 2020

The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations—also called double-vectors—have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which results in a low alignment speed. To address these issues, in this article we propose a new fast IFA method based on modified double-vectors construction and the gradient descent method. To be specific, the modified construction method is implemented by reducing the integration interval and identifying the gyroscope bias during the construction procedure, which improves the accuracy of double-vectors and IFA; the gradient descent scheme is adopted to estimate the optimal attitude of alignment without complex matrix operation, which results in the improvement of alignment speed. The effect of different sizes of mini-batch on the performance of the gradient descent method is also discussed. Extensive simulations and vehicle experiments demonstrate that the proposed method has better accuracy and faster alignment speed than the related traditional methods for the low-cost SINS/global positioning system (GPS) integrated navigation system
On the Slow-Time k-Space and its Augmentation in Doppler Radar Tomography
Authors: Tran Hai-Tan , Heading Emma , Ng Brian W.-H.
Published: January 2020

Doppler Radar Tomography (DRT) relies on spatial diversity from rotational motion of a target rather than spectral diversity from wide bandwidth signals. The slow-time k-space is a novel form of the spatial frequency space generated by the relative rotational motion of a target at a single radar frequency, which can be exploited for high-resolution target imaging by a narrowband radar with Doppler tomographic signal processing. This paper builds on a previously published work and demonstrates, with real experimental data, a unique and interesting characteristic of the slow-time k-space: it can be augmented and significantly enhance imaging resolution by signal processing. High resolution can reveal finer details in the image, providing more information to identify unknown targets detected by the radar.
UAV Mission Planning Resistant to Weather Uncertainty
Authors: Thibbotuwawa Amila , Bocewicz Grzegorz , Radzki Grzegorz , Nielsen Peter , Banaszak Zbigniew
Published: January 2020

Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning.
Capacity Bounds for Dense Massive MIMO in a Line-of-Sight Propagation Environment
Authors: de Figueiredo Felipe A. P. , Dias Claudio F. , de Lima Eduardo R. , Fraidenraich Gustavo
Published: January 2020

The use of large-scale antenna arrays grants considerable benefits in energy and spectral efficiency to wireless systems due to spatial resolution and array gain techniques. By assuming a dominant line-of-sight environment in a massive multiple-input multiple-output scenario, we derive analytical expressions for the sum-capacity. Then, we show that convenient simplifications on the sum-capacity expressions are possible when working at low and high signal-to-noise ratio regimes. Furthermore, in the case of low and high signal-to-noise ratio regimes, it is demonstrated that the Gamma probability density function can approximate the probability density function of the instantaneous channel sum-capacity as the number of served devices and base station antennas grows, respectively. A second important demonstration presented in this work is that a Gamma probability density function can also be used to approximate the probability density function of the summation of the channel’s singular values as the number of devices increases. Finally, it is important to highlight that the presented framework is useful for a massive number of Internet of Things devices as we show that the transmit power of each device can be made inversely proportional to the number of base station antennas.
Modelling Training Adaptation in Swimming Using Artificial Neural Network Geometric Optimisation
Authors: Carrard Justin , Kloucek Petr , Gojanovic Boris
Published: January 2020

This study aims to model training adaptation using Artificial Neural Network (ANN) geometric optimisation. Over 26 weeks, 38 swimmers recorded their training and recovery data on a web platform. Based on these data, ANN geometric optimisation was used to model and graphically separate adaptation from maladaptation (to training). Geometric Activity Performance Index (GAPI), defined as the ratio of the adaptation to the maladaptation area, was introduced. The techniques of jittering and ensemble modelling were used to reduce overfitting of the model. Correlation (Spearman rank) and independence (Blomqvist β) tests were run between GAPI and performance measures to check the relevance of the collected parameters. Thirteen out of 38 swimmers met the prerequisites for the analysis and were included in the modelling. The GAPI based on external load (distance) and internal load (session-Rating of Perceived Exertion) showed the strongest correlation with performance measures. ANN geometric optimisation seems to be a promising technique to model training adaptation and GAPI could be an interesting numerical surrogate to track during a season.
Impact of Environmental Regulations on Environmental Quality and Public Health in China: Empirical Analysis with Panel Data Approach
Authors: Tang Liwei , Li Ke , Jia Pinrong
Published: January 2020

Achieving high-quality environmental development through environmental regulations and thus enhancing public health is a goal of the Chinese government. Based on the panel data of 30 Chinese provinces from 1998 to 2017, this study demonstrates the co-benefits of environmental regulations on air quality, water, and public health through a panel Granger causality model and mediation effect model. The findings indicate that environmental regulations have a Granger causal effect on public health costs and air and water pollution. Furthermore, the results from the mediation effect model suggest that waste gas treatment could improve air quality, thus reducing public health costs; wastewater treatments could not only reduce public health costs through improvement of the water environment but also increase social welfare. Additionally, air pollution exhibits a greater negative externality impact on health than water pollution. Thus, environmental regulation policies should pay more attention to air pollution control. The findings of this study indicate that environmental regulations have a significant co-benefit on high-quality environmental development and public health.
Life Cycle Assessment of Iberian Traditional Pig Production System in Spain
Authors: García-Gudiño Javier , N. T. R. Monteiro Alessandra , Espagnol Sandrine , Blanco-Penedo Isabel , Garcia-Launay Florence
Published: January 2020

Traditional Iberian pig production is characterized by outdoor systems that produce animals fed with natural resources. The aim of this study was to assess the environmental impacts of such systems through Life Cycle Assessment. Environmental impacts were analysed per kilogram of live weight at farm gate. Iberian pig production in montanera had the lowest impacts for climate change (CC), acidification (AC), eutrophication (EU) and cumulative energy demand (CED), being 3.4 kg CO2 eq, 0.091 molc H+ eq, 0.046 kg PO43− eq, and 20.7 MJ, respectively, due to the strict use of natural resources (acorns and grass) during the fattening period. As Iberian farms had a greater dependence on compound feed in cebo campo, environmental impacts on CC, AC, EU and CED were 22, 17, 95 and 28% higher, respectively, than with montanera. For land occupation (LO), however, cebo campo had a lower impact (31.6 m2·year) than montanera (43.0 m2·year) system. Traditional Iberian pig production systems have environmental impacts higher than conventional systems studied in literature but are similar to other traditional systems. Based on the present assessment, it is necessary to account for the contribution of emissions resulting from the consumption of natural resources to avoid the underestimation of environmental impacts.
Making the Customer-Brand Relationship Sustainable: The Different Effects of Psychological Contract Breach Types on Customer Citizenship Behaviours
Authors: LIU Hongyan , Yang Jinglan , Chen Xiaoxi
Published: January 2020

Customer citizenship behaviours are important for a sustainable customer-brand relationship, yet little is known about the effect of psychological contract breach on citizenship behaviours. From the perspective of psychological contract theory, this research examined the impact of psychological contract breaches on customer citizenship behaviours through the mediating mechanism of psychological contract violation in the customer-brand relationship. Experiments were used to assess the effect of two types of psychological contract breaches on customer citizenship behaviours. The results show that the negative effect of a relational contract breach differs between the dimensions of citizenship behaviours. A relational contract breach has direct and indirect negative effects on recommendation behaviours and helping behaviours, but it does not affect voice behaviours. A transactional contract breach directly and negatively influences recommendation behaviours, but it has no effect on voice behaviours. A transactional contract breach indirectly increases helping behaviours through psychological contract violation. Psychological contract violation partially mediates the effect of a transactional contract breach on customer recommendation behaviours and fully mediates the effect of a relational contract breach on helping behaviours. These findings generate managerial implications for firms aiming to maintain sustainable customer-brand relationships.
Sustainability Ranking of Desalination Plants Using Mamdani Fuzzy Logic Inference Systems
Authors: Rustum Rabee , Kurichiyanil Anu Mary John , Forrest Shaun , Sommariva Corrado , Adeloye Adebayo J. , Zounemat-Kermani Mohammad , Scholz Miklas
Published: January 2020

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability.
Fuzzy Techniques for Artificial Snow Cover Optimization in the Ski Areas. Case Study: Obârșia Lotrului (Southern Carpathians, Romania)
Authors: Ilie Laurenţiu-Andrei , Comănescu Laura , Dobre Robert , Nedelea Alexandru , Săvulescu Ionuț , Bradea Ioana-Alexandra , Boloș Marcel Ioan
Published: January 2020

This paper focuses on the environmental conflicts induced by insufficient continuous snow cover on the ski areas in Romania. The case study aims envisions the area of Southern Carpathians, Latoriței Mountains, belonging to the group of Parâng Mountains. The area chosen to develop and improve the artificial snow system was conducted for in the proposed ski area, Obârşia Lotrului. This fulfilled a necessary condition (geomorphological and climatic) for the development of the ski domain. The methodology focuses on two main stages phases. In the first stage phase, based on the GIS, the areas that have shown problems in terms of continuity of the snow layer and its thickness were identified, while the second phase, there is a supposed optimization based on Fuzzy logic for the installation of artificial snow. The corresponding thickness of snow for a longer period of time can lead to a higher socio-economic efficiency, as well as the increase of the use duration of the respective ski area, and also a prevention mechanism to environmental conflicts that may arise. The proposed study supports civil society by optimizing artificial snow machines through a positive impact on water resources allocated to a ski area in order to maintain a continuous snow cover.
Modeling and Management Big Data in Databases—A Systematic Literature Review
Authors: Martinez-Mosquera Diana , Navarrete Rosa , Lujan-Mora Sergio
Published: January 2020

The work presented in this paper is motivated by the acknowledgement that a complete and updated systematic literature review (SLR) that consolidates all the research efforts for Big Data modeling and management is missing. This study answers three research questions. The first question is how the number of published papers about Big Data modeling and management has evolved over time. The second question is whether the research is focused on semi-structured and/or unstructured data and what techniques are applied. Finally, the third question determines what trends and gaps exist according to three key concepts: the data source, the modeling and the database. As result, 36 studies, collected from the most important scientific digital libraries and covering the period between 2010 and 2019, were deemed relevant. Moreover, we present a complete bibliometric analysis in order to provide detailed information about the authors and the publication data in a single document. This SLR reveal very interesting facts. For instance, Entity Relationship and document-oriented are the most researched models at the conceptual and logical abstraction level respectively and MongoDB is the most frequent implementation at the physical. Furthermore, 2.78% studies have proposed approaches oriented to hybrid databases with a real case for structured, semi-structured and unstructured data.
The Optimal Pricing Analysis for Remanufactured Notebooks in a Duopoly Environment
Authors: Tsaur Ruey-Chyn
Published: January 2020

The information technology industry plays an important role in Taiwan’s manufacturing sector, and its total notebook production ranks top in the world. The rapid development of IT products has caused many of these products to be discarded, although most of them can be recycled, remanufactured, and reused. In order to reduce the manufacture of new products and the associated carbon emissions, this study aims to discover the optimal subsidy policy for remanufactured notebooks in the green market, focusing on the pricing of remanufactured notebooks and maximizing manufacturers’ profits while retaining optimal social welfare for consumers. We use a two-stage game theory model to identify the optimal government subsidy policies for a duopoly environment. The results are based on the subsidy ratio between consumer and manufacturers, as this factor is important to the entire green supply chain; manufacturers can still reap optimal profits by only producing new or remanufactured products, and the government should be aware of the likelihood of manufacturers colluding and of the need to intervene when necessary to avoid sacrificing social welfare.
A Sustainable Approach to the Low-Cost Recycling of Waste Glass Fibres Composites towards Circular Economy
Authors: Zabihi Omid , Ahmadi Mojtaba , Liu Chao , Mahmoodi Roya , Li Quanxiang , Ghandehari Ferdowsi Mahmoud Reza , Naebe Minoo
Published: January 2020

For practical applications, both environmental and economic aspects are highly required to consider in the development of recycling of fibre reinforced polymers (FRPs) encountering their end-of-life. Here, a sustainable, low cost, and efficient approach for the recycling of the glass fibre (GF) from GF reinforced epoxy polymer (GFRP) waste is introduced, based on a microwave-assisted chemical oxidation method. It was found that in a one-step process using microwave irradiation, a mixture of hydrogen peroxide (H2O2) as a green oxidiser and tartaric acid (TA) as a natural organic acid could be used to decompose the epoxy matrix of a waste GFRP up to 90% yield. The recycled GFs with ~92.7% tensile strength, ~99.0% Young’s modulus, and ~96.2% strain-to-failure retentions were obtained when compared to virgin GFs (VGFs). This short microwave irradiation time using these green and sustainable recycling solvents makes this a significantly low energy consumption approach for the recycling of end-of-life GFRPs.
Overview of the Available Knowledge for the Data Model Definition of a Building Renovation Passport for Non-Residential Buildings: The ALDREN Project Experience
Authors: Sesana Marta Maria , Rivallain Mathieu , Salvalai Graziano
Published: January 2020

According to its strategic long-term vision, Europe wants to be a climate-neutral economy by 2050. Buildings play a crucial role in this vision, and they represent a sector with low-cost opportunities for high-level CO2 reduction. The challenge the renovation of the existing building stock, which must be increased to 3%/year, more than double compared to the current 1.2%/year. In this context, the ALliance for Deep RENovation (ALDREN) project has the goal of encouraging property owners to undertake renovation of existing buildings using a clear, robust, and comparable method. This paper aims to present the ALDREN approach and the ALDREN Building Renovation Passport (BRP), giving an overview of the connections and data links to other existing databases and certification schemes. To understand the data value potential of buildings, one requires reliable and trustworthy information. The Building Renovation Passport, introduced by the recent Energy Performance Building Directive (EPBD) recast 844/2018/EU, aims to provide this information. This paper presents the experience of the ALDREN BRP for non-residential buildings as well as the development procedure for its data model and the potential that this tool could have for the construction market. The ALDREN BRP has been structured into two main parts—BuildLog and RenoMap—with a common language that facilitates communication on the one hand and, on the other, the setting of renovation targets based on lifetime, operation, and user needs.
A Prototype that Fuses Virtual Reality, Robots, and Social Networks to Create a New Cyber–Physical–Social Eco-Society System for Cultural Heritage
Authors: Nisiotis Louis , Alboul Lyuba , Beer Martin
Published: January 2020

With the rapid development of technology and the increasing use of social networks, many opportunities for the design and deployment of interconnected systems arise that could enable a paradigm shift in the ways we interact with cultural heritage. The project described in this paper aims to create a new type of conceptually led environment, a kind of Cyber–Physical–Social Eco-Society (CPSeS) system that would seamlessly blend the real with virtual worlds interactively using Virtual Reality, Robots, and Social Networking technologies, engendered by humans’ interactions and intentions. The project seeks to develop new methods of engaging the current generation of museum visitors, who are influenced by their exposure to modern technology such as social media, smart phones, Internet of Things, smart devices, and visual games, by providing a unique experience of exploring and interacting with real and virtual worlds simultaneously. The research envisions a system that connects visitors to events and/or objects separated either in time or in space, or both, providing social meeting points between them. To demonstrate the attributes of the proposed system, a Virtual Museum scenario has been chosen. The following pages will describe the RoboSHU: Virtual Museum prototype, its capabilities and features, and present a generic development framework that will also be applicable to other contexts and sociospatial domains.
Resilience and Vulnerability of Public Transportation Fare Systems: The Case of the City of Rio De Janeiro, Brazil
Authors: Santos Tálita , Silva Marcelino Aurélio , Fernandes Vicente Aprigliano , Marsden Greg
Published: January 2020

Resilience is the ability of a system to adapt, persist, and transform as a reaction to threats, which may be external or internal to the system, while vulnerability is the state of being susceptible to harm from exposure to stresses associated with environmental and social change and from the inability to adapt. Based on a study of the threats that can affect urban mobility, we identified a gap regarding the analysis of the levels of resilience and vulnerability in the face of subsidy threats that can severely affect developing countries. This article measures the level of resilience and vulnerability due to the absence of public transport fare subsidies. For this purpose, we developed an approach based on fuzzy logic and applied it in 33 administrative regions (ARs) of the city of Rio de Janeiro, Brazil. We obtained four matrices of the levels of vulnerability and resilience of each of the regions as an origin and destination. The results show that areas nearest to the downtown region and those with high-capacity transportation available (commuter train and/or subway, systems with many transfer points) are more resilient, while a high level of vulnerability is associated with low income, negative socioeconomic indicators, and the predominance of road transportation to reach jobs. The contribution of this paper is the method applied to analyse the levels of vulnerability and resilience of public transport, which includes a threat that can cause a rupture that impacts routines and job accessibility in a region.
Suitability Assessment of the Tools Under a Three-Dimension System of Landscape Monitoring: A Case Study in the NWHS of Bogda
Authors: Ha Shangchen , Yang Zhaoping
Published: January 2020

Landscapes provide significant ecosystem service value in Natural World Heritage Sites (NWHSs) and are required to be preserved by regular monitoring and evaluation. It is vital to choose appropriate monitoring tools according to local conditions to guarantee the process is effective and efficient. This study aims to find out the spatial suitability of monitoring tools under a three-dimension system of space-based monitoring, sky-based monitoring, and ground-based monitoring. A suitability assessment was conducted from three aspects—the monitoring environment, object, and effect—from which typical differences existed among the three types of tools. Nine indicators were finalized, in which eight were classified and scored using the Delphi method with objectivity, and the remaining indicator was processed subjectively by quantifying the different monitoring effects on different landscape units by each of the tools. The method was verified using a case study in Bogda of Xinjiang Tianshan through overlay analysis in ArcGIS. The results showed an apparently stepped distribution characteristic related to altitude, where space-based monitoring zones are located in regions of high altitude, and the landscapes in low-altitude regions had the best monitoring effects using the ground-based tool and sky-based tool. Combined with the distribution characteristics of the 3-level protected zones, the results show a consistency with reality and could help planners to strategically deploy monitoring sites and allocate them advisable monitoring facilities and staffing.
Valorization of Linen Processing By-Products for the Development of Injection-Molded Green Composite Pieces of Polylactide with Improved Performance
Authors: Agüero Ángel , Lascano Diego , Garcia-Sanoguera David , Fenollar Octavio , Torres-Giner Sergio
Published: January 2020

This work reports the development and characterization of green composites based on polylactide (PLA) containing fillers and additives obtained from by-products or waste-streams from the linen processing industry. Flaxseed flour (FSF) was first produced by the mechanical milling of golden flaxseeds. The resultant FSF particles were melt-compounded at 30 wt% with PLA in a twin-screw extruder. Two multi-functionalized oils derived from linseed, namely epoxidized linseed oil (ELO) and maleinized linseed oil (MLO), were also incorporated during melt mixing at 2.5 and 5 parts per hundred resin (phr) of composite. The melt-compounded pellets were thereafter shaped into pieces by injection molding and characterized. Results showed that the addition of both multi-functionalized linseed oils successfully increased ductility, toughness, and thermal stability of the green composite pieces whereas water diffusion was reduced. The improvement achieved was related to both a plasticizing effect and, more interestingly, an enhancement of the interfacial adhesion between the biopolymer and the lignocellulosic particles by the reactive vegetable oils. The most optimal performance was attained for the MLO-containing green composite pieces, even at the lowest content, which was ascribed to the higher solubility of MLO with the PLA matrix. Therefore, the present study demonstrates the potential use of by-products or waste from flax (Linum usitatissimum L.) to obtain renewable raw materials of suitable quality to develop green composites with high performance for market applications such as rigid food packaging and food-contact disposable articles in the frame of the Circular Economy and Bioeconomy.
Optimizing the Rail Profile for High-Speed Railways Based on Artificial Neural Network and Genetic Algorithm Coupled Method
Authors: Jiang Hanwen , Gao Liang
Published: January 2020

Though the high-speed railways are seen as a sustainable form of transportation, the fact that the rail wear in high-speed railways negatively affects the running safety and riding comfort, as well as the maintenance of railways, has drawn a wide range of concerns among researchers and scholars. In order to reduce the rail wear and achieve the goal of sustainable transportation, this paper proposes an ingenious optimization program of rail profiles based on the artificial neural network (ANN) and genetic algorithm (GA) coupled method. The candidate solutions of the nonlinear GA programming model are regarded as the inputs of the trained ANN model. Meanwhile, the outputs of the trained ANN model serve as the objective functions of the GA model. The computational results show that the optimized rail profile not only has superior performances in terms of the wheel/rail wear and contact conditions, but also maintains good dynamic performances. Therefore, this study can provide the theoretical and practical basis for the design and the preventive grinding of rails in the high-speed railways. Also, the ANN-GA coupled model can be extended and further employed on the optimization of other rail profiles.
Mapping Annual Land Use and Land Cover Changes in the Yangtze Estuary Region Using an Object-Based Classification Framework and Landsat Time Series Data
Authors: Ai Jinquan , Zhang Chao , Chen Lijuan , Li Dajun
Published: January 2020

A system understanding of the patterns, causes, and trends of long-term land use and land cover (LULC) change at the regional scale is essential for policy makers to address the growing challenges of local sustainability and global climate change. However, it still remains a challenge for estuarine and coastal regions due to the lack of appropriate approaches to consistently generate accurate and long-term LULC maps. In this work, an object-based classification framework was designed to mapping annual LULC changes in the Yangtze River estuary region from 1985–2016 using Landsat time series data. Characteristics of the inter-annual changes of LULC was then analyzed. The results showed that the object-based classification framework could accurately produce annual time series of LULC maps with overall accuracies over 86% for all single-year classifications. Results also indicated that the annual LULC maps enabled the clear depiction of the long-term variability of LULC and could be used to monitor the gradual changes that would not be observed using bi-temporal or sparse time series maps. Specifically, the impervious area rapidly increased from 6.42% to 22.55% of the total land area from 1985 to 2016, whereas the cropland area dramatically decreased from 80.61% to 55.44%. In contrast to the area of forest and grassland, which almost tripled, the area of inland water remained consistent from 1985 to 2008 and slightly increased from 2008 to 2016. However, the area of coastal marshes and barren tidal flats varied with large fluctuations.
Impact of Energy Landscapes on the Abundance of Eurasian Skylark (Alauda arvensis), an Example from North Germany
Authors: Csikós Nándor , Szilassi Péter
Published: January 2020

The increasing use of biomass for energy production is reshaping landscapes into energy landscapes. Our study aims to analyze the impact of the biogas energy landscape on the abundance of Eurasian skylark. The biogas power plants have a high impact on the landscape, because of the energy crops like silage maize and rape. We analyze land-use and land-cover heterogeneity in connection with this bird species in the Federal State of Schleswig-Holstein. Three databases are used: abundance data of a typical farmland bird (Eurasian skylark), Corine land cover, and statistical land-use data from the German Agricultural Structure Survey. Several spatial analyses and statistical analyses were conducted. Generalized linear models are used with model averaging and predicted marginal effects were calculated. We estimate the changes in individuals per km2 by considering six crop types and the Shannon Diversity Index (SDI). The Eurasian skylark abundance has a significant negative correlation with the area of the inland wetlands, the Shannon Diversity Index (SDI), permanent crops, silage maize, and rape. We found significant positive correlation with the pasture, potato, and wheat. The replacement of pastures, Eurasian skylarks’ preferred habitat, with energy crops, mostly silage maize, and the ongoing homogenization of the landscape, negatively affected this species’ distribution in the study area.
Social Trust Formation and Credit Accessibility—Evidence from Rural Households in China
Authors: Zhang Tong , Liu Huiting , Liang Pinghan
Published: January 2020

Trust as a form of social capital plays an important role in improving the cooperation between agents, especially in credit lending activities. Trust building has attracted significant research interest, and gift giving has been shown to be one of its main drivers. Nonetheless, the mechanism of gift giving in the formation of trust networks and the channels through which gift giving and trust affect cooperation require further investigation. In this paper, we first separate social trust into community trust and personal trust, and we examine how gift giving affects the formation of each level of trust. We then explore how trust and gift giving affect rural households’ access to formal and informal sources of credit. Our results show that gift giving mainly helps in forming trust at the personal level rather than the community level. In turn, personal and community trust can facilitate access to informal and formal sources of credit, respectively. In addition, personal trust facilitates access to informal loans for consumption and medical expenses but not production. Overall, our findings show that gift giving is mainly used to build personal trust which facilitates access to informal lending for risk-sharing purposes.
Chinese Industrial Outward FDI Location Choice in ASEAN Countries
Authors: Ma Sheng , Xu Xinxin , Zeng Ziqiang , Wang Lin
Published: January 2020

This paper examined the location choices of Chinese outward FDI (OFDI) from 2005–2016 with a particular focus on the Association of Southeast Asian Nations (ASEAN) countries. It was found that Chinese OFDI in ASEAN countries was generally focused on areas that had large potential markets and low tax rates. Unlike previous studies, it was found that primary and secondary industry labor costs were the main motivators rather than resource-seeking. The business environment in the host countries was also found to have positive and significant effects on Chinese OFDI location choice for the agricultural, mining, construction, and information industries. The insights in this paper could provide useful suggestions for both governments and investors.
The Sustainability of Urban Food Systems: The Case of Mozzarella Production in the City of Milan
Authors: Castrica Marta , Ventura Vera , Panseri Sara , Ferrazzi Giovanni , Tedesco Doriana , Balzaretti Claudia Maria
Published: January 2020

Background: Urban food production in the developed world has recently been facing the challenge of feeding the world’s cities adequately and on a sustainable basis, and innovative models of food production can help this transition. Nevertheless, this field of research largely focuses on primary food production—so-called urban farming—while the subsequent steps of the food chain have scarcely been investigated. In this context, this study aimed to provide a preliminary evaluation of urban food processing, taking mozzarella cheese production in the city of Milan as a case study. Methods: Five urban farmers participated in a direct survey aiming at identifying how sustainable this specific production chain can be considered. Results: Results demonstrated that the concept of urban food production is really valorized through measures able to enhance the global sustainability of the food production process only in some of the dairy micro- enterprises and that the economic dimension must be considered the variable most critically involved in hampering the global sustainability of this specific food chain. Conclusions: This research suggests the need to disseminate a global governance of urban supply chains and to support local activities, which represent a sensitive and strategic sector.
Limited Non-Preemptive EDF Scheduling for a Real-Time System with Symmetry Multiprocessors
Authors: Lee Hoyoun , Lee Jinkyu
Published: January 2020

In a real-time system, a series of jobs invoked by each task should finish its execution before its deadline, and EDF (Earliest Deadline First) is one of the most popular scheduling algorithms to meet such timing constraints of a set of given tasks. However, EDF is known to be ineffective in meeting timing constraints for non-preemptive tasks (which disallow any preemption) when the system does not know the future job release patterns of the tasks. In this paper, we develop a scheduling algorithm for a real-time system with a symmetry multiprocessor platform, which requires only limited information about the future job release patterns of a set of non-preemptive tasks, called LCEDF. We then derive its schedulability analysis that provides timing guarantees of the non-preemptive task set on a symmetry multiprocessor platform. Via simulations, we demonstrate the proposed schedulability analysis for LCEDF significantly improves the schedulability performance in meeting timing constraints of a set of non-preemptive tasks up to 20.16%, compared to vanilla non-preemptive EDF.
Ciguatera Fish Poisoning: The Risk from an Aotearoa/New Zealand Perspective
Authors: Rhodes Lesley L. , Smith Kirsty F. , Murray J. Sam , Nishimura Tomohiro , Finch Sarah C.
Published: January 2020

Gambierdiscus and Fukuyoa species have been identified in Aotearoa/New Zealand’s coastal waters and G. polynesiensis, a known producer of ciguatoxins, has been isolated from Rangitāhua/Kermadec Islands (a New Zealand territory). The warming of the Tasman Sea and the waters around New Zealand’s northern subtropical coastline heighten the risk of Gambierdiscus proliferating in New Zealand. If this occurs, the risk of ciguatera fish poisoning due to consumption of locally caught fish will increase. Research, including the development and testing of sampling methods, molecular assays, and chemical and toxicity tests, will continue. Reliable monitoring strategies are important to manage and mitigate the risk posed by this emerging threat. The research approaches that have been made, many of which will continue, are summarised in this review.
Antivenom Neutralization of Coagulopathic Snake Venom Toxins Assessed by Bioactivity Profiling Using Nanofractionation Analytics
Authors: Xie Chunfang , Slagboom Julien , Albulescu Laura-Oana , Bruyneel Ben , Still Kristina B. M. , Vonk Freek J. , Somsen Govert W. , Casewell Nicholas R. , Kool Jeroen
Published: January 2020

Venomous snakebite is one of the world’s most lethal neglected tropical diseases. Animal-derived antivenoms are the only standardized specific therapies currently available for treating snakebite envenoming, but due to venom variation, often this treatment is not effective in counteracting all clinical symptoms caused by the multitude of injected toxins. In this study, the coagulopathic toxicities of venoms from the medically relevant snake species Bothrops asper, Calloselasma rhodostoma, Deinagkistrodon acutus, Daboia russelii, Echis carinatus and Echis ocellatus were assessed. The venoms were separated by liquid chromatography (LC) followed by nanofractionation and parallel mass spectrometry (MS). A recently developed high-throughput coagulation assay was employed to assess both the pro- and anticoagulant activity of separated venom toxins. The neutralization capacity of antivenoms on separated venom components was assessed and the coagulopathic venom peptides and enzymes that were either neutralized or remained active in the presence of antivenom were identified by correlating bioassay results with the MS data and with off-line generated proteomics data. The results showed that most snake venoms analyzed contained both procoagulants and anticoagulants. Most anticoagulants were identified as phospholipases A2s (PLA2s) and most procoagulants correlated with snake venom metalloproteinases (SVMPs) and serine proteases (SVSPs). This information can be used to better understand antivenom neutralization and can aid in the development of next-generation antivenom treatments.
Activation of the IRE1α Arm, but not the PERK Arm, of the Unfolded Protein Response Contributes to Fumonisin B1-Induced Hepatotoxicity
Authors: Liu Xiaoyi , Zhang Enxiang , Yin Shutao , Zhao Chong , Fan Lihong , Hu Hongbo
Published: January 2020

Previous studies by us or others have shown that endoplasmic reticulum (ER) stress was activated by fumonisin 1 (FB1) exposure, which is considered to be a critical event in the FB1-induced toxic effect. However, the detailed mechanisms underlying FB1-induced ER stress-mediated liver toxicity remain elusive. The objectives of the present study were designed to address the following issues: (1) the contribution of each arm of the unfolded protein response (UPR); (2) the downstream targets of ER stress that mediated FB1-induced liver toxicity; and (3) the relationship between ER stress and oxidative stress triggered by FB1. We also investigated whether the inhibition of ER stress by its inhibitor could offer protection against FB1-induced hepatotoxicity in vivo, which has not been critically addressed previously. The results showed that the activation of the IRE1α axis, but not of the PERK axis, of UPR contributed to FB1-induced ER stress-mediated hepatocyte toxicity; the activation of the Bax/Bak-mediated mitochondrial pathway lay downstream of IRE1α to trigger mitochondrial-dependent apoptosis in response to FB1; FB1-induced oxidative stress and ER stress augmented each other through a positive feedback mechanism; tauroursodeoxycholic acid (TUDCA)-mediated ER stress inactivation is an effective approach to counteract FB1-induced hepatotoxicity in vivo. The data of the present study allow us to better understand the mechanisms of FB1-induced hepatotoxicity.