bluuebunny/crossref_metadata_2025 huggingface dataset:
On Consensus-Based Distributed Blind Calibration of Sensor Networks
Authors: Stanković Miloš S. , Stanković Srdjan S. , Johansson Karl Henrik , Beko Marko , Camarinha-Matos Luis M.
Published: November 2018

This paper deals with recently proposed algorithms for real-time distributed blind macro-calibration of sensor networks based on consensus (synchronization). The algorithms are completely decentralized and do not require a fusion center. The goal is to consolidate all of the existing results on the subject, present them in a unified way, and provide additional important analysis of theoretical and practical issues that one can encounter when designing and applying the methodology. We first present the basic algorithm which estimates local calibration parameters by enforcing asymptotic consensus, in the mean-square sense and with probability one (w.p.1), on calibrated sensor gains and calibrated sensor offsets. For the more realistic case in which additive measurement noise, communication dropouts and additive communication noise are present, two algorithm modifications are discussed: one that uses a simple compensation term, and a more robust one based on an instrumental variable. The modified algorithms also achieve asymptotic agreement for calibrated sensor gains and offsets, in the mean-square sense and w.p.1. The convergence rate can be determined in terms of an upper bound on the mean-square error. The case when the communications between nodes is completely asynchronous, which is of substantial importance for real-world applications, is also presented. Suggestions for design of a priori adjustable weights are given. We also present the results for the case in which the underlying sensor network has a subset of (precalibrated) reference sensors with fixed calibration parameters. Wide applicability and efficacy of these algorithms are illustrated on several simulation examples. Finally, important open questions and future research directions are discussed.
Detection of Alpha-Fetoprotein in Hepatocellular Carcinoma Patient Plasma with Graphene Field-Effect Transistor
Authors: Kim Dae Hoon , Oh Hong Gi , Park Woo Hwan , Jeon Dong Cheol , Lim Ki Moo , Kim Hyung Jin , Jang Byoung Kuk , Song Kwang Soup
Published: November 2018

The detection of alpha-fetoprotein (AFP) in plasma is important in the diagnosis of hepatocellular carcinoma (HCC) in humans. We developed a biosensor to detect AFP in HCC patient plasma and in a phosphate buffer saline (PBS) solution using a graphene field-effect transistor (G-FET). The G-FET was functionalized with 1-pyrenebutyric acid N-hydroxysuccinimide ester (PBASE) for immobilization of an anti-AFP antibody. AFP was detected by assessing the shift in the voltage of the Dirac point (ΔVDirac) after binding of AFP to the anti-AFP-immobilized G-FET channel surface. This anti-AFP-immobilized G-FET biosensor was able to detect AFP at a concentration of 0.1 ng mL−1 in PBS, and the detection sensitivity was 16.91 mV. In HCC patient plasma, the biosensor was able to detect AFP at a concentration of 12.9 ng mL−1, with a detection sensitivity of 5.68 mV. The sensitivity (ΔVDirac) depended on the concentration of AFP in either PBS or HCC patient plasma. These data suggest that G-FET biosensors could have practical applications in diagnostics.
Structural Damage Identification of Bridges from Passing Test Vehicles
Authors: Yang Yang , Zhu Yuanhao , Wang Li Lei , Jia Bao Yulong , Jin Ruoyu
Published: November 2018

This paper presents two approaches for the structural damage identification of a bridge from the dynamic response recorded from a test vehicle during its passage over the bridge. Using the acceleration response recorded by the vibration sensors mounted on a test vehicle during its passage over the bridge, along with the computed displacement response, the bending stiffness of the bridge can be determined using either: (1) the frequency-domain method based on the improved directed stiffness method with the identified frequency and corresponding mode shape, or (2) the time-domain method based on the residual vector of the least squares method with a fourth-order displacement moment. By comparing the bending stiffness values identified from the vehicle-collected data for the bridge under the undamaged and damaged states that are monitored regularly by the test vehicle, the bridge damage location and severity can be identified. Through numerical simulations and field tests, the present approaches are shown to be effective and feasible.
VINS-MKF: A Tightly-Coupled Multi-Keyframe Visual-Inertial Odometry for Accurate and Robust State Estimation
Authors: Zhang Chaofan , Liu Yong , Wang Fan , Xia Yingwei , Zhang Wen
Published: November 2018

State estimation is crucial for robot autonomy, visual odometry (VO) has received significant attention in the robotics field because it can provide accurate state estimation. However, the accuracy and robustness of most existing VO methods are degraded in complex conditions, due to the limited field of view (FOV) of the utilized camera. In this paper, we present a novel tightly-coupled multi-keyframe visual-inertial odometry (called VINS-MKF), which can provide an accurate and robust state estimation for robots in an indoor environment. We first modify the monocular ORBSLAM (Oriented FAST and Rotated BRIEF Simultaneous Localization and Mapping) to multiple fisheye cameras alongside an inertial measurement unit (IMU) to provide large FOV visual-inertial information. Then, a novel VO framework is proposed to ensure the efficiency of state estimation, by adopting a GPU (Graphics Processing Unit) based feature extraction method and parallelizing the feature extraction thread that is separated from the tracking thread with the mapping thread. Finally, a nonlinear optimization method is formulated for accurate state estimation, which is characterized as being multi-keyframe, tightly-coupled and visual-inertial. In addition, accurate initialization and a novel MultiCol-IMU camera model are coupled to further improve the performance of VINS-MKF. To the best of our knowledge, it’s the first tightly-coupled multi-keyframe visual-inertial odometry that joins measurements from multiple fisheye cameras and IMU. The performance of the VINS-MKF was validated by extensive experiments using home-made datasets, and it showed improved accuracy and robustness over the state-of-art VINS-Mono.
Identifying Stops and Moves in WiFi Tracking Data
Authors: Chilipirea Cristian , Baratchi Mitra , Dobre Ciprian , Steen Maarten van
Published: November 2018

There are multiple methods for tracking individuals, but the classical ones such as using GPS or video surveillance systems do not scale or have large costs. The need for large-scale tracking, for thousands or even millions of individuals, over large areas such as cities, requires the use of alternative techniques. WiFi tracking is a scalable solution that has gained attention recently. This method permits unobtrusive tracking of large crowds, at a reduced cost. However, extracting knowledge from the data gathered through WiFi tracking is not simple, due to the low positional accuracy and the dependence on signals generated by the tracked device, which are irregular and sparse. To facilitate further data analysis, we can partition individual trajectories into periods of stops and moves. This abstraction level is fundamental, and it opens the way for answering complex questions about visited locations or even social behavior. Determining stops and movements has been previously addressed for tracking data gathered using GPS. GPS trajectories have higher positional accuracy at a fixed, higher frequency as compared to trajectories obtained through WiFi. However, even with the increase in accuracy, the problem, of separating traces in periods of stops and movements, remains similar to the one we encountered for WiFi tracking. In this paper, we study three algorithms for determining stops and movements for GPS-based datasets and explore their applicability to WiFi-based data. We propose possible improvements to the best-performing algorithm considering the specifics of WiFi tracking data.
Man-In-The-Middle Attacks in Vehicular Ad-Hoc Networks: Evaluating the Impact of Attackers’ Strategies
Authors: Ahmad Farhan , Adnane Asma , Franqueira Virginia , Kurugollu Fatih , Liu Lu
Published: November 2018

Vehicular Ad-Hoc Network (VANET), a vital component of Intelligent Transportation Systems (ITS) technology, relies on communication between dynamically connected vehicles and static Road Side Units (RSU) to offer various applications (e.g., collision avoidance alerts, steep-curve warnings and infotainment). VANET has a massive potential to improve traffic efficiency, and road safety by exchanging critical information between nodes (vehicles and RSU), thus reducing the likelihood of traffic accidents. However, this communication between nodes is subject to a variety of attacks, such as Man-In-The-Middle (MITM) attacks which represent a major risk in VANET. It happens when a malicious node intercepts or tampers with messages exchanged between legitimate nodes. In this paper, we studied the impact on network performance of different strategies which attackers can adopt to launch MITM attacks in VANET, such as fleet or random strategies. In particular, we focus on three goals of MITM attacks—message delayed, message dropped and message tampered. The simulation results indicate that these attacks have a severe influence on the legitimate nodes in VANET as the network experience high number of compromised messages, high end-to-end delays and preeminent packet losses.
A Bayesian Density Model Based Radio Signal Fingerprinting Positioning Method for Enhanced Usability
Authors: Li Zheng , Liu Jingbin , Yang Fan , Niu Xiaoguang , Li Leilei , Wang Zemin , Chen Ruizhi
Published: November 2018

Indoor navigation and location-based services increasingly show promising marketing prospects. Indoor positioning based on Wi-Fi radio signal has been studied for more than a decade because Wi-Fi, a signal of opportunity without extra cost, is extensively deployed for internet connections. Bayesian fingerprinting positioning, a classical Wi-Fi-based indoor positioning method, consists of two phases: radio map learning and position inference. Thus far, the application of Bayesian fingerprinting positioning is limited due to its poor usability; radio map learning requires an adequate number of received signal strength indication (RSSI) observables at each reference point, long-term fieldwork, and high development and maintenance costs. In this paper, based on a statistical analysis of actual RSSI observables, a Weibull–Bayesian density model is proposed to represent the probability density of Wi-Fi RSSI observables. The Weibull model, which is parameterized with three parameters that can be calculated with fewer samples, can calculate the probability density with a higher accuracy than the traditional histogram method. Furthermore, the parameterized Weibull model can simplify the radio map by storing only three parameters that can restore the whole probability density, i.e., it is not necessary to store the probability distribution based on traditionally separated RSSI bins. Bayesian positioning inference is performed in the positioning phase using probability density rather than the traditional probability distribution of predefined RSSI bins. The proposed method was implemented on an Android smartphone, and the performance was evaluated in different indoor environments. Results revealed that the proposed method enhanced the usability of Wi-Fi Bayesian fingerprinting positioning by requiring fewer RSSI observables and improved the positioning accuracy by 19–32% in different building environments compared with the classic histogram-based method, even when more samples were used.
An Integrated Machine Learning Algorithm for Separating the Long-Term Deflection Data of Prestressed Concrete Bridges
Authors: Ye Xijun , Chen Xueshuai , Lei Yaxiong , Fan Jiangchao , Mei Liu
Published: November 2018

Deflection is one of the key indexes for the safety evaluation of bridge structures. In reality, due to the changing operational and environmental conditions, the deflection signals measured by structural health monitoring systems are greatly affected. These ambient changes in the system often cover subtle changes in the vibration signals caused by damage to the system. The deflection signals of prestressed concrete (PC) bridges are regarded as the superposition of different effects, including concrete shrinkage, creep, prestress loss, material deterioration, temperature effects, and live load effects. According to multiscale analysis theory of the long-term deflection signal, in this paper, an integrated machine learning algorithm that combines a Butterworth filter, ensemble empirical mode decomposition (EEMD), principle component analysis (PCA), and fast independent component analysis (FastICA) is proposed for separating the individual deflection components from a measured single channel deflection signal. The proposed algorithm consists of four stages: (1) the live load effect, which is a high-frequency signal, is separated from the raw signal by a Butterworth filter; (2) the EEMD algorithm is used to extract the intrinsic mode function (IMF) components; (3) these IMFs are utilized as input in the PCA model and some uncorrelated and dominant basis components are extracted; and (4) FastICA is applied to derive the independent deflection component. The simulated results show that each individual deflection component can be successfully separated when the noise level is under 10%. Verified by a practical application, the algorithm is feasible for extracting the structural deflection (including concrete shrinkage, creep, and prestress loss) only caused by structural damage or material deterioration.
Optimal Routing for Time-Driven EH-WSN under Regular Energy Sources
Authors: Galmés Sebastià
Published: November 2018

The recent provision of energy-harvesting capabilities to wireless sensor networks (WSN) has entailed the redefinition of design objectives. Specifically, the traditional goal of maximizing network lifetime has been replaced by optimizing network performance, namely delay and throughput. The present paper contributes to this reformulation by considering the routing problem for the class of time-driven energy-harvesting WSN (EH-WSN) under regular or quasi-periodic energy sources. In particular, this paper shows that the minimum hop count (MHC) criterion maximizes the average duty cycle that can be sustained by nodes in this type of scenarios. This is a primary objective in EH-WSN, since large duty cycles lead to enhanced performance. Based on a previous result, a general expression is first obtained that gives mathematical form to the relationship between duty cycle and traffic load for any node in a time-driven EH-WSN fed by a regular energy source. This expression reveals that the duty cycle achievable by a node decreases as its traffic load increases. Then, it is shown that MHC minimizes the average traffic load over the network, and thus it maximizes the average duty cycle of nodes. This result is numerically validated via simulation by comparison with other well-known routing strategies. Accordingly, this paper suggests assigning top priority to the MHC criterion in the development of routing protocols for time-driven EH-WSN under regular energy sources.
Sensitive and Reproducible Gold SERS Sensor Based on Interference Lithography and Electrophoretic Deposition
Authors: Hwang June , Yang Minyang
Published: November 2018

Surface-enhanced Raman spectroscopy (SERS) is a promising analytical tool due to its label-free detection ability and superior sensitivity, which enable the detection of single molecules. Since its sensitivity is highly dependent on localized surface plasmon resonance, various methods have been applied for electric field-enhanced metal nanostructures. Despite the intensive research on practical applications of SERS, fabricating a sensitive and reproducible SERS sensor using a simple and low-cost process remains a challenge. Here, we report a simple strategy to produce a large-scale gold nanoparticle array based on laser interference lithography and the electrophoretic deposition of gold nanoparticles, generated through a pulsed laser ablation in liquid process. The fabricated gold nanoparticle array produced a sensitive, reproducible SERS signal, which allowed Rhodamine 6G to be detected at a concentration as low as 10−8 M, with an enhancement factor of 1.25 × 105. This advantageous fabrication strategy is expected to enable practical SERS applications.
Validity and Repeatability of Single-Sensor Loadsol Insoles during Landing
Authors: Peebles Alexander T. , Maguire Lindsay A. , Renner Kristen E. , Queen Robin M.
Published: November 2018

Clinically feasible methods for quantifying landing kinetics could help identify patients at risk for secondary anterior cruciate ligament injuries. The purpose of this study was to evaluate the validity and between-day repeatability of the loadsol insole during a single-hop and bilateral stop-jump. Thirty healthy recreational athletes completed seven single-hops and seven stop-jumps while simultaneous loadsol (100 Hz) and force plate (1920 Hz) measurements were recorded. Peak impact force, loading rate, and impulse were computed for the dominant limb, and limb symmetry was calculated between limbs for each measure. All outcomes were compared between the loadsol and force plate using intraclass correlation coefficients (ICC) and Bland–Altman plots. Fifteen participants completed a second day of testing to assess between-day repeatability of the loadsol. Finally, an additional 14 participants completed the first day of testing only to assess the validity of the newest generation loadsol, which sampled at 200 Hz. At 100 Hz, validity ICC results were moderate to excellent (0.686–0.982), and repeatability ICC results were moderate to excellent (0.616–0.928). The 200 Hz loadsol demonstrated improved validity ICC (0.765–0.987). Bland–Altman plots revealed that the loadsol underestimated load measures. However, this bias was not observed for symmetry outcomes. The loadsol device is a valid and repeatable tool for evaluating kinetics during landing.
An Optimized Colorimetric Readout Method for Lateral Flow Immunoassays
Authors: Park Jongwon
Published: November 2018

Despite its broad penetration of various markets, the quantitative lateral flow immunoassay (LFIA) suffers from sensitivity issues in some cases. To solve this problem, an optimized colorimetric readout method for LFIA quantification is proposed in this study. An assay reader device utilizing a color camera and an analysis method using a Bayer filtered image were developed. Spectrometric measurements of the assay test line were performed to determine the color channel that contains the test line information and effectively minimizes noise. The change in the intensity ratio with increasing concentration of the target substance in the sample was largest in the green channel. The linear range of the output curve ranged from 0 to 10 ng/mL, and the detection limit was 2 ng/mL. The suggested instrumentation and analysis methods are expected to effectively resolve the low-sensitivity problems of the former LFIA systems and to offer other prospective functionalities for LFIA quantification.
Cold Plasma as an Innovative Construction Method of Voltammetric Biosensor Based on Laccase
Authors: Malinowski Szymon , Wardak Cecylia , Jaroszyńska-Wolińska Justyna , Herbert P. Anthony F. , Panek Rafał
Published: November 2018

Development of new, faster methods of biosensor construction is a huge challenge for current science and industry. In this work, biosensor construction was carried out using a new soft plasma polymerization (SPP) method in which a bio-recognition layer of laccase enzyme was polymerized and bonded to a glassy carbon electrode (GCE) substrate under atmospheric pressure with a corona discharge jet. Laccase belongs to the oxidoreductase enzyme group with four copper atoms in its active center. Application of the corona SPP plasma method allows reduction of the time needed for biosensor construction from several hours to minutes. The presented work includes optimization of the laccase bio-recognition layer deposition time, structural studies of the deposited laccase layer, as well as study of the fabricated biosensor applicability for the determination of Rutin in real pharmaceutical samples. This method produces a biosensor with two linear ranges from 0.3 μmol/dm3 to 0.5 μmol/dm3 and from 0.8 μmol/dm3 to 16 μmol/dm3 of Rutin concentration. Results shown in this work indicate that application of the one-step, corona SPP method enables biosensor construction with comparable analytical parameters to biosensors fabricated by conventional, multi-step, wet methods.
Conformal and Disposable Antenna-Based Sensor for Non-Invasive Sweat Monitoring
Authors: Eldamak Angie R. , Fear Elise C.
Published: November 2018

This paper presents a feasibility study for a non-wearable, conformal, low cost, and disposable antenna-based sensor for non-invasive hydration monitoring using sweat. It is composed of a patch antenna implemented on a cellulose filter paper substrate and operating in the range 2–4 GHz. The paper substrate can absorb liquids, such as sweat on the skin, through two slots incorporated within the antenna structure. Thus, the substrate dielectric properties are altered according to the properties of the absorbed liquid. Changes in reflection-based measurements are used to analyze salt solutions and artificial sweat, specifically the amount of sampled solution and the sodium chloride (NaCl) concentration. Using the shift in resonant frequency and magnitude of the reflection coefficient, NaCl concentrations in the range of 8.5–200 mmol/L, representing different hydration states, are detected. The measurements demonstrate the feasibility of using microwave based measurements for hydration monitoring using sweat.
Monitoring Candida parapsilosis and Staphylococcus epidermidis Biofilms by a Combination of Scanning Electron Microscopy and Raman Spectroscopy
Authors: Hrubanova Kamila , Krzyzanek Vladislav , Nebesarova Jana , Ruzicka Filip , Pilat Zdenek , Samek Ota
Published: November 2018

The biofilm-forming microbial species Candida parapsilosis and Staphylococcus epidermidis have been recently linked to serious infections associated with implanted medical devices. We studied microbial biofilms by high resolution scanning electron microscopy (SEM), which allowed us to visualize the biofilm structure, including the distribution of cells inside the extracellular matrix and the areas of surface adhesion. We compared classical SEM (chemically fixed samples) with cryogenic SEM, which employs physical sample preparation based on plunging the sample into various liquid cryogens, as well as high-pressure freezing (HPF). For imaging the biofilm interior, we applied the freeze-fracture technique. In this study, we show that the different means of sample preparation have a fundamental influence on the observed biofilm structure. We complemented the SEM observations with Raman spectroscopic analysis, which allowed us to assess the time-dependent chemical composition changes of the biofilm in vivo. We identified the individual spectral peaks of the biomolecules present in the biofilm and we employed principal component analysis (PCA) to follow the temporal development of the chemical composition.
Female Genital Mutilation in Nigeria: A Persisting Challenge for Women’s Rights
Authors: Yaya Sanni , Ghose Bishwajit
Published: November 2018

Although considered a violation of human rights, female genital mutilation (FGM) is a commonly accepted practice in Nigeria in the ritual and sociocultural context of the population. In recent years, there have been strong policy actions by Nigerian legislature to curb this practice. Despite that, FGM continues to be a widespread phenomenon. In this study, we aimed to report on the prevalence of FGM, women’s attitude towards this practice, and its association with selected sociodemographic factors. Methods: Nigeria Demographic and Health Surveys conducted in 2003, 2008 and 2013 provided the data for this study. The participants were married women aged between 15 and 49 years. Owing to the clustered nature of the data, a complex survey plan was created to account for cluster effects and sampling weights. Data were analysed using bivariate and multivariate regression techniques. Results: Overall prevalence of FGM was 38.9% (95% CI = 36.4–40.1), and that among their daughters was 17.4% (95% CI = 15.3–19.7). There has been a substantial increase in the prevalence of FGM in 2013 compared to its 2003 level. Respondents who had undergone circumcision were more likely to have their daughters circumcised. In all three surveys, almost all of the circumcisions were performed by traditional practitioners. In the regression analysis, respondent’s age, area and region of residency, religious affiliation, educational status, and household wealth appeared to be significant predictors of FGM. Conclusion: In Nigeria, FGM remains a widely prevalent phenomenon with an increasing number of women experiencing this practice. Important regional and socioeconomic disparities were observed in the prevalence which merit urgent policy attention.
The Rise of the Androgynous Princess: Examining Representations of Gender in Prince and Princess Characters of Disney Movies Released 2009–2016
Authors: Hine Benjamin , England Dawn , Lopreore Katie , Skora Horgan Elizabeth , Hartwell Lisa
Published: November 2018

Previous quantitative research examining Disney movies has highlighted that whilst prince characters display largely balanced gender profiles, princesses exhibit biased gender role portrayals—performing mostly feminine characteristics, rarely participating in rescue behavior, and concluding movies in romantic relationships with the prince. However, such research, as well as public commentary, has also suggested that princess characters in movies released across the 2000s and 2010s may have more positive gender role portrayals. This study aimed to test these assertions by utilizing content coding analysis to examine the behavioral characteristics, rescue behavior, and romantic conclusions of prince and princess characters in five iconic Disney films released between 2009 and 2016 (The Princess and the Frog, Tangled, Brave (released under Pixar), Frozen, and Moana). Comparisons were also made with earlier titles to assess historical changes. Results showed that princesses in “2000s to 2010s” movies exhibited an almost equal number of masculine and feminine behaviors, thus demonstrating more egalitarian profiles over time. In contrast, princes appeared to adopt a more feminine behavioral profile in later movies. In addition, characters engaged in equal numbers of rescue behaviors, and princesses were more likely to remain single in “2000s to 2010s” movies. Results therefore suggest that Disney is indeed presenting more diverse, androgynous, balanced characters to viewers, and the theoretical and practical implications for the socialization of young child viewers are discussed.
Nitrogen Mineralization and Microbial Biomass Dynamics in Different Tropical Soils Amended with Contrasting Organic Resources
Authors: Ansong Omari Richard , Bellingrath-Kimura Dorothea Sonoko , Fujii Yoshiharu , Sarkodee-Addo Elsie , Appiah Sarpong Kwame , Oikawa Yosei
Published: November 2018

The use of location-specific and underutilized organic residues (OR) as soil amendments in small-holder agro-ecosystems is promising. Six ORs (Leucaena leucocephala, Centrosema pubescens, Gliricidia sepium, Pueraria phaseoloides, Azadirachta indica, and Theobroma cacao) were amended to three tropical soils each at 24 mg g−1 dry soil in 120-day incubation study to estimate their nitrogen (N) mineralization and microbial biomass carbon (C) dynamics. Inorganic N contents varied among ORs, soil type and incubation days. Regardless of soil type, Gliricidia had the highest inorganic N among the studied ORs. Mineralization rate of 1.4 to 1.5 mg N kg−1 soil day−1 was observed for Lego and Tec soils, respectively, and was twice higher than Nya soil. However, Nya soil released higher inorganic N than Tec and Lego soils, implying high N mineralization efficiency in the former. Consistent soil pH increase was respectively observed for Theobroma and Pueraria treatments in all soils. Moreover, Theobroma and Pueraria amendments showed the highest soil microbial biomass C (MBC) at the end of the incubation. The assessed soil properties likely affected by the dominant edaphic factors and management influenced differences in MBC and dissolved organic carbon (DOC) while OR quality indices controlled N mineralization. Thus, we conclude that soil properties and OR type are important factors for optimal utilization of organic resources.
Organic versus Conventional Farming—A Paradigm for the Sustainable Development of the European Countries
Authors: Cristache Silvia-Elena , Vuță Mariana , Marin Erika , Cioacă Sorin-Iulian , Vuţă Mihai
Published: November 2018

Although organic farming is an important topic for society, at the European level there have been few achievements so far. Despite its constant increase, the demand for organic food in Europe is outweighing the development of this sector. As such, we aim to assess the interaction between conventional and organic agriculture, as well as their impact on the value of agricultural production at the European level. The main objective of this article is the assessment of the impact of organic farming, as compared with conventional agriculture, on sustainable development of European countries. Therefore, we used panel models based on data collected from the Eurostat database. We found that an increase of 1% of the organic farming areas will generate a contraction in agricultural production of 0.278%, whereas a 1% increase in the production of fertilizers would generate an increase of 0.260% in agriculture production. Moreover, an increase of 1% in the production of plant protection substances and in gross capital formation would generate increases of 0.1190% and 0.0933%, respectively, in agriculture production. The obtained results depend mainly on the characteristics of work on land, as some agricultural engineering methods (crop rotation, pest control, use of fertilizers etc.) influence productivity and production.
Impact of Property Tax on Housing-Market Disequilibrium in Different Regions: Evidence from Taiwan for the period 1982–2016
Authors: Lin Sheng-Hau , Li Jia-Hsun , Hsieh Jing-Chzi , Huang Xianjin , Chen Jia-Tsong
Published: November 2018

Although Taiwan has had a unique property tax system for a long time, oversupply and increasing prices have persisted in the regional market during recent decades. In order to shed light on this problem, this study investigated the impact of property taxation on housing markets in different regions from a disequilibrium viewpoint based on the stock-flow model. The panel data of 20 counties or cities in Taiwan for the period from 1982 to 2016 was examined. The empirical findings verified that housing price was the most important factor for influencing the long-run housing supply and demand in regions both with and without oversupply. The low interest rate policy was an important factor driving the long-run housing demand, but only in over-supply regions. The current property tax system cannot impact the long-run housing demand, only the short-run demand in both regions. Moreover, the property tax cannot effectively disturb the supply behavior in the long-run in both regions. This study also confirmed that housing-market disequilibrium existed in regions both with and without oversupply, making up the gap. The property tax’s impact on the adjustment speed to long-run equilibrium in over-supply regions was weaker than under-supply regions.
The Effect of Ideology on Attitudes toward GM Food Safety among Chinese Internet Users
Authors: Zhang Yue , Sun Yingying
Published: November 2018

This study explores the causal relationship between Internet users’ ideologies and their corresponding attitudes to genetically modified (GM) food safety. Using the 2015 Chinese Internet User Survey data (N = 3780) as a representative sample of Internet users from China, the study investigates factors influencing people’s attitudes to GM food safety. Multinomial Logistic Regression Models are applied to examine the effects of demographic features (gender, age, education, family annual income, location, CPC membership, and occupation) and ideological factors (general ideology, political ideology, economic ideology, and cultural ideology) on attitudes to GM food safety. The results demonstrate that the percentage of people whose attitude is that “GM food is risky” (35.1%) surpasses those who think “GM food is safe” (20.4%). The young generation respondents think that GM food is safe, while those with higher levels of income and education are more inclined to view GM food as risky. In addition, public sector employees tend to think that GM food is risky. Respondents characterized with right-wing ideology in general tend to regard GM food as safe, compared to left-wing ideologists. However, their attitude varies in different ideological dimensions of politics, economics, and culture. This paper contributes new insights into understanding ideological influences on science development and sustainability.
Self-Assessment Method for Sustainability Implementation in Product Innovation
Authors: Schulte Jesko , Hallstedt Sophie Isaksson
Published: November 2018

Companies, striving towards an effective and systematic integration of a strategic sustainability perspective in product innovation, need to treat the implementation of necessary processes and tools, as well as their continuous improvement, as a project in itself. An efficient way to measure the current sustainability implementation level in the organization, as well as guidance for progression, is required. To meet this need, a novel self-assessment was developed, which provides companies with a tool to assess and visualize their current capabilities in relation to key elements for successful sustainability integration in the product innovation process. It includes a scale of different sustainability implementation levels to support building a roadmap for systematic implementation, and to measure progress over time. This research is based on results from previous descriptive work within the area of sustainable product development and learning from applying strategic and tactical assessment tools for eco-design and sustainability maturity. Besides the contribution to practice, this study also contributes to knowledge by specifying detailed aspects for each key element that must be considered to guide sustainability integration. Also, insights from applying different existing tools in real cases are provided. The newly-developed self-assessment method was applied and validated at two case companies. Independent and continuous use of it by the companies beyond this particular study indicate the practical value of the method.
Ancient Use of Natural Geothermal Resources: Analysis of Natural Cooling of 16th Century Villas in Costozza (Italy) as a Reference for Modern Buildings
Authors: Ferrucci Margherita , Peron Fabio
Published: November 2018

The geothermal cooling system of six 16th century villas in Costozza (Vicenza, Italy) is analysed and modelled using computational fluid dynamics and referring to in-field monitoring data. The system passively cools the villas in summertime by means of underground ducts connected to the caves present in the nearby hills. It still perfectly works in Villa Aeolia, which is analysed here in more detail. The outcomes permit us to better understand the functioning conditions and to improve the conservation of the villas as a whole. Furthermore, the ancient cooling system can be used as a reference for how geothermal renewable resources can be used to improve indoor comfort and limit energy consumption in modern buildings in a temperate climate. A macroscopic analysis of the global airflow system as well as a detailed analysis of Villa Aeolia are developed. All results are validated with analytical methods, numerical methods, and with past experimental records. The system can provide fresh airflow rates that cool the walls of the room and maintain the temperature below 20 ° C even on hot summer days. An advantage is that the system works in a self-adaptive way, the airflow increases when the outdoor temperature increases. This self-adjustment allows us to compare the cooling system to a modern environmental control system.
Analysis of the Resilience of Common-Pool Resources during Globalization: The Case of Jeju Common Ranches in Korea
Authors: Kim Kyungmin , Kim Juhee , Cho Kijong , Kim Jeong-Gyu , Hyun Seunghun
Published: November 2018

A common-pool resource (CPR) is a type of good consisting of a natural or human-made resource system. Jeju common ranches are historical CPRs located in Jeju Province where mid-mountainous grassland has been shared for livestock farming by the members of adjacent villages since the 10th century. Because of the recent globalization movement, the number of ranches has decreased from 126 in the 1940s to only 53 in 2015; while the majority of the ranches did not survive the transformation, others have remained active by adopting various solutions. In this study, we analyzed the administrative characteristics of the CPRs to explain their current status (i.e., extinction or continuance as a common property) using logistic regression analysis. From this analysis, four statistically meaningful variables were extracted using a forward stepwise selection method; these include the type of ranch management, ratio of land area to population, number of internal committees in the village, and number of local government grants. These variables correlate well with previously recognized ‘community resilience dimensions’ and can be used to explain the fate of the Jeju common ranches during the study period. This study elucidates what community dimensions should be fortified to promote the resilience of Jeju common ranches in order to effectively cope with the on-going effects of globalization.
Development of a Standard Brownfield Definition, Guidelines, and Evaluation Index System for Brownfield Redevelopment in Developing Countries: The Case of Pakistan
Authors: Ahmad Naveed , Zhu Yuming , Ibrahim Muhammad , Waqas Muhammad , Waheed Abdul
Published: November 2018

Brownfield is post-industrial soil resulting from different anthropogenic activities and located in urban centers of cities. Due to the scarcity of urban land and the complexity of renovating old cities, and considering that brownfield research in Pakistan is still in its infancy, defining and evaluating brownfield is necessary for solving environmental issues and promoting sustainable development. Therefore, this study aims to develop a pioneer consensus-based brownfield definition, guidelines, and an evaluation index system to evaluate brownfield redevelopment in Pakistan. Initially, a comprehensive literature review was performed to gather key elements of brownfield definitions and create an evaluation index system. These indicators were further evaluated by different experts through the Delphi Method to develop a final questionnaire. Then, data were collected from relevant stakeholders. An illustrative example using three ideal schemes (housing society, eco-industrial park, and commercial market) is described to apply the evaluation index system. A new methodology combining Triangular Fuzzy Numbers (TFNs) and Grey Relational Analysis (GRA) was introduced to assess three ideal schemes. Finally, a pioneer brownfield definition, guidelines, and evaluation index system for brownfield redevelopment were developed, and a further index system was verified through an illustrative example. The standard brownfield definition, guidelines, and established index system is based on the Pakistani context. Due to changes in rules and regulation, and different land characteristics, these findings cannot be generalized to all developing countries. Therefore, further studies must validate the results in their own context. This study will foster brownfield redevelopment implementation in Pakistan and promote sustainable development.
Simultaneous Removal of NOx and SO2 through a Simple Process Using a Composite Absorbent
Authors: Fang Ping , Tang Zijun , Chen Xiongbo , Zhong Peiyi , Huang Jianhang , Tang Zhixiong , Cen Chaoping
Published: November 2018

In this work, the feasibility of the simultaneous removal of NOx and SO2 through a simple process using a composite absorbent (NaClO2/Na2S2O8) was evaluated. Factors affecting the removal of NOx and SO2, such as NaClO2 and Na2S2O8 concentrations, solution temperature, the initial pH of solution, gas flow rate, and SO2, NO, and O2 concentrations were studied, with a special attention to NOx removal. Results indicate that a synergistic effect on NOx removal has been obtained through combination of NaClO2 and Na2S2O8. NaClO2 in the solution played a more important role than did Na2S2O8 for the removal of NOx. The above factors had an important impact on the removal of NOx, especially the solution temperature, the initial pH of the solution, and the oxidant concentrations. The optimum experimental conditions were established, and a highest efficiency of NOx removal of more than 80% was obtained. Meanwhile, tandem double column absorption experiments were conducted, and a NOx removal efficiency of more than 90% was reached, using NaOH solution as an absorbant in the second reactor. A preliminary reaction mechanism for NOx and SO2 removal was deduced, based on experimental results. The composite absorbent has the potential to be used in the wet desulfurization and denitration process, to realize the synergistic removal of multi-pollutants.
Socio-Economic Factors Influencing Small-Scale Farmers’ Market Participation: Case of Rice Producers in Dano
Authors: Yaméogo Thomas B. , Bossa Aymar Y. , Torou Bio M. , Fusillier Jean-Louis , Da Dapola E. C. , Yira Yacouba , Serpantié Georges , Somé Fourvouon , Dama-Balima Mariam M.
Published: November 2018

This paper explores the key factors influencing market participation decisions among smallholder lowland rice growers. Data were collected through purposive sampling technique. A total of 127 rice growers, from 16 lowlands (developed and traditional lowlands), was selected. Descriptive statistics and the probit regression model were used to analyse the data. The statistical analysis revealed significant differences in yields between developed and traditional lowlands rice plots (“lowland development effect”). The regression results showed that farmers’ behaviours were not gender neutral; male producers were more likely to take part in the market as compared to their female counterparts, implying a “gender effect”. With respect to the effect of membership in farmers’ organization, the results indicate that farmers’ involvement in an organization, was in general negatively associated to their market participation decisions. However, farmers from lowlands with functional rice producers’ organizations were more likely to sell their products in the market. Interestingly, this study also highlighted that lowland rice producers’ ability to generate a marketable surplus (at least 20 kg/person/year) positively influence their market participation decision. As hypothesized, the results revealed that farmers who have access to potential buyers of the output (secured market outlets) were less likely to produce rice for self-consumption.
The Impact of the New Rural Pension Scheme on Retirement Sustainability in China: Evidence of Regional Differences in Formal and Informal Labor Supply
Authors: Lin Benxi , Lin Zongjian , Zhang Yu Yvette , Liu Weiping
Published: November 2018

This paper evaluates the effect of China’s New Rural Pension Scheme (NRPS) on the retirement sustainability in forms of formal labor supply and informal labor supply in terms of care of grandchildren, using data from China Health and Retirement Longitudinal Study (CHARLS). We explore the regional differences of the NRPS effect on labor supply between the West and the other regions of China. Our analysis shows that rural Western China has a more severe problem of “ceaseless toil” compared to the rest of the country. We find that NRPS improves the “ceaseless toil” situation of the Chinese rural elderly especially in Western China. Our results suggest the need to increase the amount of NRPS payment, and to develop a region-specific pension programs in China.
Is Overtourism Overused? Understanding the Impact of Tourism in a City Context
Authors: Koens Ko , Postma Albert , Papp Bernadett
Published: November 2018

In less than two years, the concept of overtourism has come to prominence as one of the most discussed issues with regards to tourism in popular media and, increasingly, academia. In spite of its popularity, the term is still not clearly delineated and remains open to multiple interpretations. The current paper aims to provide more clarity with regard to what overtourism entails by placing the concept in a historical context and presenting results from a qualitative investigation among 80 stakeholders in 13 European cities. Results highlight that overtourism describes an issue that is multidimensional and complex. Not only are the issues caused by tourism and nontourism stakeholders, but they should also be viewed in the context of wider societal and city developments. The article concludes by arguing that while the debate on overtourism has drawn attention again to the old problem of managing negative tourism impacts, it is not well conceptualized. Seven overtourism myths are identified that may inhibit a well-rounded understanding of the concept. To further a contextualized understanding of overtourism, the paper calls for researchers from other disciplines to engage with the topic to come to new insights.
Small Black/White Hole Stability and Dark Matter
Authors: Rovelli Carlo , Vidotto Francesca
Published: November 2018

We show that the expected lifetime of white holes formed as remnants of evaporated black holes is consistent with their production at reheating. We give a simple quantum description of these objects and argue that a quantum superposition of black and white holes with large interiors is stable, because it is protected by the existence of a minimal eigenvalue of the area, predicted by Loop Quantum Gravity. These two results support the hypothesis that a component of dark matter could be formed by small black hole remnants.
Fast Tracks and Roadblocks for Zika Vaccines
Authors: Ghaffar Khairunnisa Abdul , Ng Lisa F.P. , Renia Laurent
Published: November 2018

In early 2014, a relatively obscure virus, the Zika virus, made headlines worldwide following an increase in the number of congenital malformations. Since then, research on Zika virus, treatment and vaccines have progressed swiftly with various drugs being repurposed and vaccines heading into clinical trials. Nonetheless, the need for a vaccine is crucial in order to eradicate this re-emerging arthropod-borne virus which remained silent since its first discovery in 1947. In this review, we focused on how the inconspicuous virus managed to spread, the key immunological factors required for a vaccine and the various vaccine platforms that are currently being studied.