bluuebunny/crossref_metadata_2025 huggingface dataset:
Determination of Significant Wave Heights Using Damping Coefficients of Attenuated GNSS SNR Data from Static and Kinematic Observations
Authors: Roggenbuck Ole , Reinking Jörg , Lambertus Tomke
Published: February 2019

Currently, GNSS reflectometry based on the signal-to-noise ratio (SNR) has become an established tool in ocean remote sensing. Here, the distance between an antenna and the water surface is measured by analyzing the oscillation of the SNR observation. Due to the antenna gain pattern, this oscillation is more pronounced for satellite signals coming from low elevation angles. Additionally, the sea surface roughness is related to the attenuation of the SNR oscillation. Hence, the significant wave height (SWH) can be estimated by analyzing the SNR signal. In this work, a method is presented with which the SWH can be calculated from the attenuation’s damping coefficient of the SNR observations measured with surface-based receivers. The method’s usability is demonstrated using data from a static antenna operated in the German Bight and with data from a ship-based antenna. The estimated SWH values were validated against numerical wave model data. For both experiments, a high correlation was found.
UAV-Based High Throughput Phenotyping in Citrus Utilizing Multispectral Imaging and Artificial Intelligence
Authors: Ampatzidis Yiannis , Partel Victor
Published: February 2019

Traditional plant breeding evaluation methods are time-consuming, labor-intensive, and costly. Accurate and rapid phenotypic trait data acquisition and analysis can improve genomic selection and accelerate cultivar development. In this work, a technique for data acquisition and image processing was developed utilizing small unmanned aerial vehicles (UAVs), multispectral imaging, and deep learning convolutional neural networks to evaluate phenotypic characteristics on citrus crops. This low-cost and automated high-throughput phenotyping technique utilizes artificial intelligence (AI) and machine learning (ML) to: (i) detect, count, and geolocate trees and tree gaps; (ii) categorize trees based on their canopy size; (iii) develop individual tree health indices; and (iv) evaluate citrus varieties and rootstocks. The proposed remote sensing technique was able to detect and count citrus trees in a grove of 4,931 trees, with precision and recall of 99.9% and 99.7%, respectively, estimate their canopy size with overall accuracy of 85.5%, and detect, count, and geolocate tree gaps with a precision and recall of 100% and 94.6%, respectively. This UAV-based technique provides a consistent, more direct, cost-effective, and rapid method to evaluate phenotypic characteristics of citrus varieties and rootstocks.
Evaluation of Orbit, Clock and Ionospheric Corrections from Five Currently Available SBAS L1 Services: Methodology and Analysis
Authors: Nie Zhixi , Zhou Peiyuan , Liu Fei , Wang Zhenjie , Gao Yang
Published: February 2019

To meet the demands of civil aviation and other precise navigation applications, several satellite-based augmentation systems (SBASs) have been developed around the world, such as the Wide Area Augmentation System (WAAS) for North America, the European Geostationary Navigation Overlay Service (EGNOS) for Europe, the Multi-functional Satellite Augmentation System (MSAS) for Japan, the GPS (Global Positioning System) Aided GEO Augmented Navigation (GAGAN) for India, and the System for Differential Corrections and Monitoring (SDCM) for Russia. The SBASs broadcast messages to correct satellite orbit, clock, and ionosphere errors to augment the GPS positioning performance. In this paper, SBAS orbit, clock and ionospheric corrections are evaluated. Specifically, the orbit, clock and ionospheric corrections derived from SBAS messages are comprehensively evaluated using data collected from the above mentioned systems over 181 consective days. The evaluation indicates that the EGNOS outperforms other systems with signal-in-space range error (SISRE) at 0.645 m and ionospheric correction accuracy at 0.491 m, respectively. Meanwhile, the accuracy of SDCM is comparable to EGNOS with SISRE of 0.650 m and ionospheric correction accuracy of 0.523 m. For WAAS, the SISRE is 0.954 m and the accuracy of ionospheric correction is 0.505 m. The accuracies of the SBAS corrections from the MSAS and GAGAN systems, however, are significantly worse than those of others. The SISREs are 1.931 and 1.325 m and the accuracies of ionospheric corrections are 0.795 and 0.858 m, for MSAS and GAGAN, respectively. At the same time, GPS broadcast orbit, clock and ionospheric corrections are also evaluated. The results show that there are no significant improvements in the SISRE of the broadcast navigation data by applying SBAS corrections. On the other hand, the accuracy of SBAS ionospheric corrections is still much better than GPS broadcast ionospheric corrections, which could still be beneficial for single-frequency users.
Resonating Shell: A Spherical-Omnidirectional Ultrasound Transducer for Underwater Sensor Networks
Authors: Sadeghpour Sina , Meyers Sebastian , Kruth Jean-Pierre , Vleugels Jozef , Kraft Michael , Puers Robert
Published: February 2019

This paper presents the design and fabrication process of a spherical-omnidirectional ultrasound transducer for underwater sensor network applications. The transducer is based on the vibration of two hemispheres with a thickness of 1 mm and an outer diameter of 10 mm, which are actuated by two piezoelectric ring elements. Since the ultrasound wave is generated by the vibration of the two hemispheres, a matching layer is not required. Silicon Carbide (SiC) is used as the material of the hemispherical shells of the transducer. The shells were fabricated by laser sintering as an additive manufacturing method, in which the hemispheres were built layer by layer from a powder bed. All manufactured transducers with an outer dimension of 10 × 14.2 mm and a center frequency of 155 kHz were measured in a water tank by a hydrophone or in mutual communication. The circumferential source level was measured to vary less than 5dB. The power consumption and the insertion loss of the transducer, ranging from 100 μ W to 2.4 mW and 21.2 dB, respectively, along with all other measurements, prove that the transducer can transmit and receive ultrasound waves omnidirectionally at tens of centimeters intervals with a decent power consumption and low actuation voltage.
Co3O4/Al-ZnO Nano-composites: Gas Sensing Properties
Authors: Fort Ada , Panzardi Enza , Vignoli Valerio , Hjiri Mokhtar , Aida Mohamed Salah , Mugnaini Marco , Addabbo Tommaso
Published: February 2019

In this paper, the gas sensing properties of metal oxide nano-powder composites are studied and modeled. The gas sensing properties of mixtures of two different metal oxide nanoparticles, prepared via low-cost routes, are investigated. The responses to both an oxidizing (NO2) and a reducing gas (CO) are analyzed. The tested composites are obtained by mixing a different percentage of a p-type metal oxide, Co3O4, with moderate responses to NO2 at about 200 °C and to CO at high temperature (above 260 °C), with n-type Al-doped ZnO, which is characterized by a large but unstable response towards NO2 around 160 °C and a moderate response towards CO around 200 °C. In the oxides mixtures, p-n heterojunctions are formed by the juxtaposition of an n-type and a p-type grain in contact. Consequently, the electronic conductivity is modified and the obtained composite materials show novel characteristics with respect to the base materials. This indicates that predicting the behavior of the composites from those of their components is not possible and it suggests that the hetero-junction behavior has to be studied to understand the sensing properties of the composite materials. The obtained results indicate that the composites containing a significant amount of hetero-junctions exhibit a stable response to NO2 at room temperature and significant responses towards CO at 160 °C.
ID Insertion and Data Tracking with Frequency Offset for Physical Wireless Parameter Conversion Sensor Networks
Authors: Takyu Osamu , Shirai Keiichiro , Ohta Mai , Fujii Takeo
Published: February 2019

As the applications of the internet of things are becoming widely diversified, wireless sensor networks require real-time data reception, accommodation of access from several sensors, and low power consumption. In physical wireless parameter conversion sensor networks (PhyC-SN), all the sensors use frequency shift keying as the modulation scheme and then access the channel to the fusion center, simultaneously. As a result, the fusion center can recognize the statistical tendency of all the sensing results at a time from the frequency spectrum of the received signal. However, the information source, i.e., the sensor, cannot be specified from the received signal because no ID-indicating sensor is inserted to the signal. The data-tracking technique for tracing the time continuity of the sensing results is available for decomposing the sequence of the sensing results per sensor but the error tracking, which is a wrong recognition between the sensing results and the sensor, occurs owing to the similarity of the sensing results. This paper proposes the sensing result separation technique using a fractional carrier frequency offset (CFO) for PhyC-SN. In the proposed scheme, the particular fractional CFO is assigned to each user and it is useful for the ID specifying sensor. The fractional CFO causes inter-carrier interference (ICI). The ICI cancellation of the narrowband wireless communications is proposed. The two types of data-tracking techniques are proposed and are selectively used by the fusion center. Since the proposed data-tracking technique is multi-dimensional, high accuracy of data tracking is achieved even under the similar tendency of the sensing results. Based on computer simulation, we elucidate the advantage of the proposed sensing results separation.
A New Data Fusion Algorithm for Wireless Sensor Networks Inspired by Hesitant Fuzzy Entropy
Authors: Wang Jiayao , Tawose Olamide Timothy , Jiang Linhua , Zhao Dongfang
Published: February 2019

The wireless sensor network (WSN) is mainly composed of a large number of sensor nodes that are equipped with limited energy and resources. Therefore, energy consumption in wireless sensor networks is one of the most challenging problems in practice. On the other hand, data fusion can effectively decrease data redundancy, reduce the amount of data transmission and energy consumption in the network, extend the network life cycle, improve the utilization of bandwidth, and thus overcome the bottleneck on energy and bandwidth consumption. This paper proposes a new data fusion algorithm based on Hesitant Fuzzy Entropy (DFHFE). The new algorithm aims to reduce the collection of repeated data on sensor nodes from the source, and strives to utilize the information provided by redundant data to improve the data reliability. Hesitant fuzzy entropy is exploited to fuse the original data from sensor nodes in the cluster at the sink node to obtain higher quality data and make local decisions on the events of interest. The sink nodes periodically send local decisions to the base station that aggregates the local decisions and makes the final judgment, in which process the burden for the base station to process all the data is significantly released. According to our experiments, the proposed data fusion algorithm greatly improves the robustness, accuracy, and real-time performance of the entire network. The simulation results demonstrate that the new algorithm is more efficient than the state-of-the-art in terms of both energy consumption and real-time performance.
Static and Dynamic Activity Detection with Ambient Sensors in Smart Spaces
Authors: Shelke Sagar , Aksanli Baris
Published: February 2019

Convergence of Machine Learning, Internet of Things, and computationally powerful single-board computers has boosted research and implementation of smart spaces. Smart spaces make predictions based on historical data to enhance user experience. In this paper, we present a low-cost, low-energy smart space implementation to detect static and dynamic human activities that require simple motions. We use low-resolution (4 × 16) and non-intrusive thermal sensors to collect data. We train six machine learning algorithms, namely logistic regression, naive Bayes, support vector machine, decision tree, random forest and artificial neural network (vanilla feed-forward) on the dataset collected in our lab. Our experiments reveal a very high static activity detection rate with all algorithms, where the feed-forward neural network method gives the best accuracy of 99.96%. We also show how data collection methods and sensor placement plays an important role in the resulting accuracy of different machine learning algorithms. To detect dynamic activities in real time, we use cross-correlation and connected components of thermal images. Our smart space implementation, with its real-time properties, can be used in various domains and applications, such as conference room automation, elderly health-care, etc.
Process Management in IoT Operating Systems: Cross-Influence between Processing and Communication Tasks in End-Devices
Authors: Rodriguez-Zurrunero Roberto , Utrilla Ramiro , Rozas Alba , Araujo Alvaro
Published: February 2019

The emergence and spread of Internet of Things (IoT) technologies along with the edge computing paradigm has led to an increase in the computational load on sensor end-devices. These devices are now expected to provide high-level information instead of just raw sensor measurements. Therefore, the processing tasks must share the processor time with the communication tasks, and both of them may have strict timing constraints. In this work, we present an empirical study, from the edge computing perspective, of the process management carried out by an IoT Operating System (OS), showing the cross-influence between the processing and communication tasks in end-devices. We have conducted multiple tests in two real scenarios with a specific OS and a set of wireless protocols. In these tests, we have varied the processing and communication tasks timing parameters, as well as their assigned priority levels. The results obtained from these tests demonstrate that there is a close relationship between the characteristics of the processing tasks and the communication performance, especially when the processing computational load is high. In addition, these results also show that the computational load is not the only factor responsible for the communication performance degradation, as the relationship between the processing tasks and the communication protocols timing parameters also plays a role. These conclusions should be taken into account for future OSs and protocol developments.
A Hardware-Friendly Optical Flow-Based Time-to-Collision Estimation Algorithm
Authors: Shi Cong , Dong Zhuoran , Pundlik Shrinivas , Luo Gang
Published: February 2019

This work proposes a hardware-friendly, dense optical flow-based Time-to-Collision (TTC) estimation algorithm intended to be deployed on smart video sensors for collision avoidance. The algorithm optimized for hardware first extracts biological visual motion features (motion energies), and then utilizes a Random Forests regressor to predict robust and dense optical flow. Finally, TTC is reliably estimated from the divergence of the optical flow field. This algorithm involves only feed-forward data flows with simple pixel-level operations, and hence has inherent parallelism for hardware acceleration. The algorithm offers good scalability, allowing for flexible tradeoffs among estimation accuracy, processing speed and hardware resource. Experimental evaluation shows that the accuracy of the optical flow estimation is improved due to the use of Random Forests compared to existing voting-based approaches. Furthermore, results show that estimated TTC values by the algorithm closely follow the ground truth. The specifics of the hardware design to implement the algorithm on a real-time embedded system are laid out.
Microfluidic Microwave Sensor for Detecting Saline in Biological Range
Authors: Kilpijärvi Joni , Halonen Niina , Juuti Jari , Hannu Jari
Published: February 2019

A device for measuring biological small volume liquid samples in real time is appealing. One way to achieve this is by using a microwave sensor based on reflection measurement. A prototype sensor was manufactured from low cost printed circuit board (PCB) combined with a microfluidic channel made of polymethylsiloxane (PDMS). Such a sensor was simulated, manufactured, and tested including a vacuum powered sample delivery system with robust fluidic ports. The sensor had a broad frequency band from 150 kHz to 6 GHz with three resonance frequencies applied in sensing. As a proof of concept, the sensor was able to detect a NaCl content of 125 to 155 mmol in water, which is the typical concentration in healthy human blood plasma.
Sensor Fusion-Based Cooperative Trail Following for Autonomous Multi-Robot System
Authors: Geng Mingyang , Liu Shuqi , Wu Zhaoxia
Published: February 2019

Autonomously following a man-made trail in the wild is a challenging problem for robotic systems. Recently, deep learning-based approaches have cast the trail following problem as an image classification task and have achieved great success in the vision-based trail-following problem. However, the existing research only focuses on the trail-following task with a single-robot system. In contrast, many robotic tasks in reality, such as search and rescue, are conducted by a group of robots. While these robots are grouped to move in the wild, they can cooperate to lead to a more robust performance and perform the trail-following task in a better manner. Concretely, each robot can periodically exchange the vision data with other robots and make decisions based both on its local view and the information from others. This paper proposes a sensor fusion-based cooperative trail-following method, which enables a group of robots to implement the trail-following task by fusing the sensor data of each robot. Our method allows each robot to face the same direction from different altitudes to fuse the vision data feature on the collective level and then take action respectively. Besides, considering the quality of service requirement of the robotic software, our method limits the condition to implementing the sensor data fusion process by using the “threshold” mechanism. Qualitative and quantitative experiments on the real-world dataset have shown that our method can significantly promote the recognition accuracy and lead to a more robust performance compared with the single-robot system.
Roller Bearing Performance Degradation Assessment Based on Fusion of Multiple Features of Electrostatic Sensors
Authors: Zhang Ying , Wang Anchen , Zuo Hongfu
Published: February 2019

This paper presents a new method to assess the performance degradation of roller bearings based on the fusion of multiple features, with the aim of improving the early degradation detection ability of the electrostatic monitoring system. At first, a set of feature parameters of the electrostatic monitoring system indicating the normal state of the bearings are extracted from the perspective of the time domain, frequency domain and complexity. Then, the parameter set is processed to reduce the dimensions and eliminate the redundancy using spectral regression. With the processed features, a Gaussian mixed model is established to gauge the health of the bearing, providing the distance value obtained using Bayesian inference as a quantitative indicator for assessing the performance degradation. The method is applied to access the life of a bearing in which the mechanic fatigue is artificially accelerated. The test results show that the proposed method can better reflect the degradation process of the bearing compared to other evaluation methods. This enables the electrostatic monitoring technique to detect the degradation of the bearing earlier than the vibration monitoring, providing a powerful tool for the condition monitoring of roller bearings.
Gastrocnemius Medialis Architectural Properties at Rest and During Stretching in Female Athletes with Different Flexibility Training Background
Authors: Donti Olyvia , Panidis Ioli , Terzis Gerasimos , Bogdanis Gregory C.
Published: February 2019

Background: This study examined gastrocnemius medialis (GM) architectural properties and ankle joint range of motion (ROM) between female athletes with different flexibility training background. Methods: Elite rhythmic gymnasts (n = 10) were compared to national level volleyball athletes (n = 10). Fascicle length, pennation angle and muscle thickness at the medial and the distal part of GM, and ankle ROM were measured at rest and during 1 min of static stretching. Results: At rest, rhythmic gymnasts displayed longer fascicles compared to volleyball athletes, at the medial (5.93 ± 0.27 vs. 4.74 ± 0.33 mm, respectively, p = 0.001) and the distal part of GM (5.63 ± 0.52 vs. 4.57 ± 0.51 mm, respectively, p = 0.001), smaller pennation angle at the medial part (22.4 ± 2.5 vs. 25.8 ± 2.4°; respectively, p = 0.001) and greater ankle angle (121.7 ± 4.1 vs. 113.2 ± 3.7°, respectively, p = 0.001). During the 1 min of static stretching, gymnasts displayed greater fascicle elongation at the distal part (p = 0.026), greater maximal ankle dorsiflexion (p < 0.001) and muscle tendon junction displacement (p < 0.001) with no difference between groups in pennation angles (p > 0.145), muscle thickness (p > 0.105), and fascicle elongation at mid-belly (p = 0.063). Conclusions: Longer muscle fascicles at rest and greater fascicle elongation at the distal part of GM may contribute to the greater ankle ROM observed in rhythmic gymnasts.
Variations of Groundwater Quality in the Multi-Layered Aquifer System near the Luanhe River, China
Authors: Guo Qiaona , Zhou Zhifang , Huang Guojiao , Dou Zhi
Published: February 2019

Nitrate pollution is an environmental problem in the North China Plain. This paper investigates the variation of groundwater levels and nitrate concentrations in an alluvial fan of the Luanhe river, northeast of the North China Plain. Three transects perpendicular to the riverbank were selected to investigate the exchange between river water and groundwater, and nitrate concentration with its isotopic composition (δ15N-NO3 and δ18O-NO3). The results showed that the groundwater level decreased slightly during the dry season, and increased regularly during the period of river stage rise. The groundwater is recharged by the river over 10 months each year. The nitrate concentration in the groundwater and river water varied with seasons. The nitrate concentration of groundwater in wells near the river is affected by the river water, which varied in basically the same way as the river. The nitrate concentrations in the zone of groundwater level depression cone were lower than those in the wells near the river, due to the long-term pumping of groundwater. However, the nitrate concentrations of river water have little influence on those of groundwater in wells far from the river. The values of δ15N-NO3 and the relationship between the two isotopes (δ15N-NO3 and δ18O-NO3) suggested that NO3-N was mainly attributable to sewage, livestock manure and natural soil organic matter. Due to the existence of a groundwater depression cone near the river, nitrate contamination can be transported into the aquifer with the flow. The average time lag of nitrate migration from the river to the zone of groundwater level depression cone is different in different sections, which shows an increasing trend from the upstream to downstream along the river, with an average of two to six months. It is mainly related to the stratigraphic structure, the migration distance, the hydraulic conductivities of the aquifer and the riverbed sediment. Compared with the case of considering the silt layer, the time lag of nitrate migration is greater than that of the case of ignoring the silt layer. The results will provide useful information for detecting nitrate concentrations in the alluvial fan area of the Luanhe river, northeast of the NCP (North China Plain).
Reflecting Disaster Risk in Development Indicators
Authors: Mochizuki Junko , Naqvi Asjad
Published: February 2019

Disasters triggered by hazards, such as floods, earthquakes, droughts, and cyclones, pose significant impediments to sustainable development efforts in the most vulnerable and exposed countries. Mainstreaming disaster risk is hence seen as an important global agenda as reflected in the Sustainable Development Goals (SDGs) and the Sendai Framework for Disaster Risk Reduction (SFDRR) 2015–2030. Yet, conventional development indicators remain largely negligent of the potential setbacks that may be posed by disaster risk. This article discusses the need to reflect disaster risk in development indicators and proposes a concept disaster risk-adjusted human development index (RHDI) as an example. Globally available national-level datasets of disaster risk to public and private assets (including health, educational facilities, and private housing) is combined with an estimate of expenditure on health, education, and capital formation to construct an RHDI. The RHDI is then analyzed across various regions and HDI groups, and contrasted with other HDI variants including inequality-adjusted HDI (IHDI) and the gender-specific female HDI (FHDI) to identify groups of countries where transformational disaster risk reduction (DRR) approaches may be necessary.
Motivational Climate towards the Practice of Physical Activity, Self-Concept, and Healthy Factors in the School Environment
Authors: Castro-Sánchez Manuel , Zurita-Ortega Félix , García-Marmol Eduardo , Chacón-Cuberos Ramón
Published: February 2019

The objective of the present study was to define and contrast an explanatory model relating the motivational climate, body mass index, and adherence to a Mediterranean diet with the self-concept of school children. A further objective was to analyze the existing relationships between the variables included in the developed model according to sex, using a multi-group structural equation analysis. In the study, a total of 734 school children, of both sexes, reported their perceived motivational climate towards sport, body mass index, adherence to a Mediterranean diet, and self-concept. These children were aged between 10 and 12 years old and attended public school in the province of Granada (Spain). The multi-group structural equation model developed demonstrated an excellent fit to the empirical data (χ2 = 228.179; DF = 40; p < 0.001; CFI = 0.965; NFI = 0.958; IFI = 0.968; RMSEA = 0.048). The findings identified a direct negative relationship between the ego climate and the task climate. Furthermore, an inverse relationship was found between the task climate and body mass index, and a direct relationship was found between the ego climate and body mass index. Meanwhile, Mediterranean diet adherence was directly related to the task climate and negatively related to the ego climate. The main conclusions of the present study highlight the positive effects of a task-oriented motivational climate and adherence to a Mediterranean diet, with regards to body mass index. Furthermore, a task-oriented motivational climate and a lower body mass index are related to a more positive self-concept.
TYPHABOARD in the Restoration of Historic Black Sea Houses in Bulgaria
Authors: Georgiev Georgi , Krus Martin , Loretz Carina , Theuerkorn Werner
Published: February 2019

TYPHABOARD is a sustainable construction and thermal insulation board made of cattail (lat. typha) and magnesite as a binder. It is characterized by a unique combination of high mechanical strength, highly insulating properties, relatively high diffusion openness, inflammability, and a sustainable lifecycle. The TYPHABOARD concept includes ecological benefits related to the systematic planting of the raw material typha in Bulgaria, the production of TYPHABOARD, and its application as a stabilizing, insulating and passive indoor climate controlling element in the framework structure of the historic typology of the Black Sea House. The entire technological and organizational process provides a sustainable solution for the operation of peat areas by planting typha (which acts as a natural water and ground filter), for the engagement of work forces in structurally underdeveloped regions, for sustainable ecological and social regional development, as well as for the sustainable retrofit of existing historic Black Sea Houses. The building and ecological system TYPHABOARD can be successfully introduced and applied in Bulgaria. In addition to the scientific and the practical study, the political eligibility of this was proved and officially permitted by the relevant public bodies in Bulgaria.
Carbon-Regulated EOQ Models with Consumers’ Low-Carbon Awareness
Authors: Tao Zhimiao , Xu Jiuping
Published: February 2019

In the context of a low-carbon economy, firms must make positive responses in their operation management, including inventory management. Carbon-emission regulation policies have marked their influence on the optimization of low-carbon inventory systems. In addition to regulation policies, consumers’ low-carbon awareness can also influence inventory systems by affecting demand. This study investigates the influence of regulation policies and consumers’ low-carbon awareness on optimal order size, emission levels, and total costs. Two widely used regulation policies, i.e., the carbon-tax mechanism and cap-and-trade mechanism, are incorporated into the classical Economic Order Quantity (EOQ) model. Analytical conclusions were obtained by optimization methods to indicate the influences of regulation policies and consumers’ low-carbon awareness. Our study implies that inventory systems under different regulation policies perform similarly except with regard to total cost. Numerical examples provide more support for these analytical conclusions. Some managerial insights can be derived from the analytical conclusions and numerical examples.
Context-Adapted Urban Planning for Rapid Transitioning of Personal Mobility towards Sustainability: A Systematic Literature Review
Authors: Nikulina Varvara , Simon David , Ny Henrik , Baumann Henrikke
Published: February 2019

Sustainability related challenges in mobility planning have been recognised at the international level, and the urgency for change has been widely discussed among scholars. However, there seems to be no general agreement on the best ways to pursue such change. To seek answers to the question of how to pursue change, this study analysed the development of the broad research fields of mobility, urban planning and transitions, and the overlap of these bodies of literature. Both academic and non-academic literatures were covered. By means of a systematic literature review, as well as bibliometric studies, several prominent research themes that address change from planning and transition perspectives were identified. Moreover, these themes describe different viewpoints and challenges in mobility planning. These include planning and policy for sustainable mobility and accessibility, backcasting and scenario planning, indicators in planning, modes of transport, decision-making, studies of global North and global South, as well as overarching themes of equity, equality and justice, roles of institutions, and co-production of knowledge. Strategies for staying up to date with these fields were also identified. In the literature covered, the temporal dimension in mobility planning was described in four different ways, but little was found about how accelerated transitions towards sustainable mobility can be achieved. Further knowledge gaps were identified in relation to behavioural change, policy development, institutionalisation of planning capacity, and social sustainability in mobility planning. This created an outline for possible future studies.
A Community-Based Agro-Food Hub Model for Sustainable Farming
Authors: Manikas Ioannis , Malindretos George , Moschuris Socrates
Published: February 2019

This conceptual paper focuses on the Agro-Food Hub paradigm as the main enabler for the sustainable development of agro-food Small and Medium Enterprises (SMEs) in the context of the currently established agro-food systems. This paper is based on a shared knowledge-driven research that presents different approaches/types of Agro-Food Hubs, providing useful insights into the strategic, operational and institutional approaches of the topic. After the illustration of the main approaches for the Agro-Food Hubs met in the literature, a holistic Agro-Food Hubs model was proposed (the Agro-Food Sustainability Knowledge Hub model), incorporating the main principles and functional guidelines within the framework of the Corporate Social Responsibility (CSR) and Sustainable Supply Chain Management. This study is in line with the demographic, economic and social prospects for the 2050 and the European Economic and Social Committee decision for “An EU Industrial Policy for the Food and Drinks Sector” adopted on 4 May 2015. In particular, since the majority of research in the past focused on large organizations, this paper is expected to enlighten the problems emerged from current applied practices together with the opportunities for potential synergies among agricultural SMEs, through the utilization of alternative sustainable channels of distribution and value creation, such as the Agro-Food Hubs.
Could Biomass Derived Fuels Bridge the Emissions Gap between High Speed Rail and Aviation?
Authors: Prussi Matteo , Konti Aikaterini , Lonza Laura
Published: February 2019

Aviation is a steadily growing sector, which largely contributes to transport greenhouse gas (GHG) emissions. When High Speed Rail (HSR) and aviation are considered as alternative options, HSR proves to be a more environmentally friendly mode of transport. Public available data have been used in order to calculate the emission profiles on two selected intra-European routes (London–Paris and Frankfurt–Amsterdam) by HSR and air. As expected, the air mode results in higher GHG emissions and solutions for mitigating its impact have been analyzed and suggested. Biomass Derived Fuels (BDF) has a limited, up to now, potential, to fill the existing gap in terms of emissions with rail. Moreover, BDF reduction in GHG emissions is accompanied with by an increase in fuel cost. Finally, the cost per tonne of avoided CO2e by using BDF—which values 186 €/t—has been compared with the prices of the European Union (EU) Emission Trading System (ETS) allowances and, from a purely economic perspective, this market based measure still seems a preferable option to curb the GHG emissions of the air mode.
The Effects of Consumers’ Perceived Values on Intention to Purchase Upcycled Products
Authors: Yu Somi , Lee Jieun
Published: February 2019

As concerns around today’s environmental problems increase, there is a growing need for consumers to accelerate their sustainable behaviors relating to product disposal such as product reuse and product life extension. The purpose of this study was to investigate consumers’ value perceptions and their intentions to purchase upcycled products. This study identified the total perceived utility of upcycled products as six values that influence different levels of product attitude, which, in turn, affect purchase intention. In addition, the study examined the moderating role of purchase experience in the relationship between perceived value and product attitude. Survey data from 413 people in the United States were used to test our hypotheses. We found that three values (i.e., green, emotional, aesthetic) had a significantly positive effect on both product attitude and purchase intention. The moderating effect of purchase experience was found only on the paths between green and functional values and product attitude. The findings offer implications for academics, practitioners, and policymakers in designing strategies that encourage people to purchase upcycled products. We conclude that organizations should design strategies that maximize the emotional and aesthetic values of upcycled products using varied and engaging content, such as storytelling, based on each product’s background.
The Influence of Knowledge on Residents’ Perceptions of the Impacts of Overtourism in P2P Accommodation Rental
Authors: Gutiérrez-Taño Desiderio , Garau-Vadell Joan B. , Díaz-Armas Ricardo J.
Published: February 2019

Accommodation rental activity through P2P platforms has experienced exponential growth in recent years, and in many cities has generated discomfort among residents who hold it responsible for overtourism and other negative impacts. Understanding residents’ perceptions and attitudes is fundamental for the sustainable development of tourism activity. This study investigates the influence of residents’ “knowledge” of the activity on their perception of impacts and their attitude towards it. Using the social exchange theory as a theoretical framework, this paper compares the data obtained in the world-class destination Majorca, in 2015 and 2017. Data was gathered through a convenience sampling procedure with self-administered questionnaires. The results confirm the influence of this variable on the perception of the impacts and its moderating effect on residents’ attitudes. The study confirms the influence of a greater level of knowledge of the activity on the perception of the impacts and on attitudes and it generally results in a greater perception of the costs and a lesser impact of benefits. The implications in terms of destination management are also discussed.
The Indirect-Utility Criterion for Ranking Opportunity Sets over Time
Authors: García-Sanz María Dolores , Alcantud José Carlos Rodríguez
Published: February 2019

A preference defined on a set of alternatives can be extended to a preference on the subsets of alternatives (named opportunity sets) in different ways. We specifically consider the application of the indirect-utility (IU) criterion in various stages, when both the alternatives and the preferences can change over time. In other words, we maintain the symmetry over time as far as criteria are concerned, but neither in the preferences, nor in the alternatives. We characterize this criterion by three testable axioms. Our study bears comparison with Krause (Economic Theory, 2008) for the two-period model.
Optical Transparency and Local Electronic Structure of Yb-Doped Y2O3 Ceramics with Tetravalent Additives
Authors: Zhidkov Ivan S. , Kukharenko Andrey I. , Maksimov Roman N. , Finkelstein Larisa D. , Cholakh Seif O. , Osipov Vladimir V. , Kurmaev Ernst Z.
Published: February 2019

The results of optical transmission and X-ray core-level spectra measurements of Yb:Y2O3 ceramics with different tetravalent sintering additives (ZrO2, CeO2 and HfO2) fabricated from nanopowders (produced by the laser ablation method) and then annealed at 1400 ℃ in air for 2 h are presented. It is found that the transmission values for ZrO2- and HfO2-doped ceramics at the lasing wavelengths are higher than those of CeO2-doped samples. The X-ray photoelectron spectra (XPS) O 1s spectra show that the relative intensity of oxygen defect peak detected for 3Yb:Y2O3 + 5CeO2 ceramics decreases substantially and consistently compared to that of 5Yb:Y2O3 + 5HfO2 and 3Yb:Y2O3 + 5ZrO2 samples. This can be attributed to a more complete filling of oxygen vacancies due to annealing-induced oxygen diffusion into the highly defective sintered ceramics. The measurements of XPS Ce 3d spectra showed that the insufficiently complete filling of the oxygen vacancies in the 3Yb:Y2O3 + 5CeO2 compound is due to the appreciable presence of trivalent cerium ions.
The Pentagonal Fuzzy Number:Its Different Representations, Properties, Ranking, Defuzzification and Application in Game Problems
Authors: Chakraborty Avishek , Mondal Sankar Prasad , Alam Shariful , Ahmadian Ali , Senu Norazak , De Debashis , Salahshour Soheil
Published: February 2019

In this paper, different measures of interval-valued pentagonal fuzzy numbers (IVPFN) associated with assorted membership functions (MF) were explored, considering significant exposure of multifarious interval-valued fuzzy numbers in neoteric studies. Also, the idea of MF is generalized somewhat to nonlinear membership functions for viewing the symmetries and asymmetries of the pentagonal fuzzy structures. Accordingly, the construction of level sets, for each case of linear and nonlinear MF was also carried out. Besides, defuzzification was undertaken using three methods and a ranking method, which were also the main features of this framework. The developed intellects were implemented in a game problem by taking the parameters as PFNs, ultimately resulting in a new direction for modeling real world problems and to comprehend the uncertainty of the parameters more precisely in the evaluation process.
Ultrarelativistic Gas with Zero Chemical Potential
Authors: Mata-Pacheco Daniel , Ares de Parga Gonzalo , Angulo-Brown Fernando
Published: February 2019

In this work, we propose a set of conditions such that an ultrarelativistic classical gas can present a photon-like behavior. This is achieved by assigning a zero chemical potential to the ultrarelativistic ideal gas. The resulting behavior is similar to that of a Wien photon gas. It is found to be possible only for gases made of very lightweight particles such as neutrinos, as long as we treat them as classical particles, and it depends on the spin degeneracy factor. This procedure allows establishing an analogy between an evaporating gas and the cavity radiation.
Assessing the Human Resource in Science and Technology for Asian Countries: Application of Fuzzy AHP and Fuzzy TOPSIS
Authors: Chou Ying-Chyi , Yen Hsin-Yi , Dang Van Thac , Sun Chia-Chi
Published: February 2019

The fuzzy analytic hierarchy process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are extremely beneficial when a decision-making process is complex. The reason is that AHP and TOPSIS can prioritize multiple-choice criteria into a hierarchy by assessing the relative importance of criteria and can thus generate an overall ranking of the alternatives. This study uses fuzzy AHP and fuzzy TOPSIS to evaluate the human resource in science and technology (HRST) performance of Southeast Asian countries. The fuzzy TOPSIS analysis indicates that Singapore, South Korea, and Taiwan have similarities in their desired levels of HRST performance. That is, these three countries have better HRST performances than other Southeast Asian countries.
Regional Councils in a Global Context: Council Types and Council Elements
Authors: Growe Anna , Jemming Marilu
Published: February 2019

Propelled by the increasing global competition for location qualities and production factors of (economic) regions in the age of globalization, regional councils have been introduced on sub-national levels in a number of countries. However, the conditions to develop and to govern these regional spaces vary massively in global comparison. Based on three types of elements for the well-functioning of regional councils, in this study, ten regional councils across the globe have been analysed and compared by carrying out qualitative web researches and expert’s interviews. Results show that although huge differences between the political organizations in the globally selected case studies exist, two main forms and two sub-types of councils—with a specific functional orientation—can be identified. The aim of the paper is to provide an analytical framework that can be used in analysing regional councils or in processes to develop regional councils further.
Ebola Virus Isolation Using Huh-7 Cells has Methodological Advantages and Similar Sensitivity to Isolation Using Other Cell Types and Suckling BALB/c Laboratory Mice
Authors: Logue James , Vargas Licona Walter , Cooper Timothy K. , Reeder Becky , Byrum Russel , Qin Jing , Deiuliis Murphy Nicole , Cong Yu , Bonilla Amanda , Sword Jennifer , Weaver Wade , Kocher Gregory , Olinger Gene G. , Jahrling Peter B. , Hensley Lisa E. , Bennett Richard S.
Published: February 2019

Following the largest Ebola virus disease outbreak from 2013 to 2016, viral RNA has been detected in survivors from semen and breast milk long after disease recovery. However, as there have been few cases of sexual transmission, it is unclear whether every RNA positive fluid sample contains infectious virus. Virus isolation, typically using cell culture or animal models, can serve as a tool to determine the infectivity of patient samples. However, the sensitivity of these methods has not been assessed for the Ebola virus isolate, Makona. Described here is an efficiency comparison of Ebola virus Makona isolation using Vero E6, Huh-7, monocyte-derived macrophage cells, and suckling laboratory mice. Isolation sensitivity was similar in all methods tested. Laboratory mice and Huh-7 cells were less affected by toxicity from breast milk than Vero E6 and MDM cells. However, the advantages associated with isolation in Huh-7 cells over laboratory mice, including cost effectiveness, sample volume preservation, and a reduction in animal use, make Huh-7 cells the preferred substrate tested for Ebola virus Makona isolation.
Tackling the “New Normal”: A Resilience Assessment Method Applied to Real-World Urban Water Systems
Authors: Nikolopoulos Dionysios , van Alphen Henk-Jan , Vries Dirk , Palmen Luc , Koop Stef , van Thienen Peter , Medema Gertjan , Makropoulos Christos
Published: February 2019

The water sector is, currently and for the foreseeable future, challenged by rising levels of uncertainty in demand and availability of water, in a context of aging infrastructure and limited investment. In order to support strategic planning, water companies need a way to assess how their system behaves when faced with a range of changing conditions (climatic trends, asset deterioration, behavioral patterns, etc.) as well as accidents/incidents and/or extreme events (wildcards). In this study, a resilience assessment methodology was demonstrated, with ‘stress tests’ alternative water system configurations (including systems designed with decentralized or distributed philosophies) under a range of scenarios and extreme events. A ‘resilience profile graph’ was developed to quantify the performance of each configuration. The methodology was applied to the real-world urban water system of Oasen, which supplies the eastern part of the Province of South Holland, where the current system configuration and two potential future configurations were tested (one decentralized and one distributed). We show how the concept of resilience, operationalized through this methodology, can assist long term decision making and support strategic infrastructure planning.