bluuebunny/crossref_metadata_2025 huggingface dataset:
Modifications of Polymeric Membranes Used in Guided Tissue and Bone Regeneration
Authors: Florjanski Wojciech , Orzeszek Sylwia , Olchowy Anna , Grychowska Natalia , Wieckiewicz Wlodzimierz , Malysa Andrzej , Smardz Joanna , Wieckiewicz Mieszko
Published: May 2019

Guided tissue/bone regeneration (GTR/GBR) is a widely used procedure in contemporary dentistry. To achieve the required results of tissue regeneration, soft tissues that reproduce quickly are separated from the slow-growing bone tissue by membranes. Many types of membranes are currently in use, but none of them fulfil all of the desired features. To address this issue, further research on developing new membranes with better separation characteristics, such as membrane modification, is needed. Many of the current innovative modified materials are still in the phase of in vitro and experimental studies. A collective review on new trends in membrane modification to GTR/GBR is needed due to the widespread use of polymeric membranes and the constant development in the field of dentistry. Therefore, the aim of this review was to present an overview of polymeric membrane modifications to the GTR/GBR reported in the literature. The authors searched databases, including PubMed, SCOPUS, Web of Science, and OVID, for relevant studies that were published during 1999–2019. The following keywords were used: guided tissue regeneration, membranes, coating, and modification. A total of 17 papers were included in this review. Furthermore, the articles were divided into three groups that were based on the type of membrane modification: antibiotic coating, ion-use modifications, and others modifications, thus providing an overview of current existing knowledge in the field and encouraging further research. The results of included studies on modified barrier membranes seem to be promising, both in terms of safety and benefits for patients. However, modifications result in a large spectrum of effects. Further clinical studies are needed on a large group of patients to clearly confirm the effects that were observed in animal and in vitro studies.
Human Rights Issues Arising from the Implementation of Sharia Law on the Minority of Western Thrace—ECtHR Molla Sali v. Greece, Application No. 20452/14, 19 December 2018
Authors: Koumoutzis Nikos , Papastylianos Christos
Published: May 2019

The Molla Sali case, recently heard by the ECtHR, concerns the compatibility of the implementation of Sharia in the family and personal relations of the Muslims of Western Thrace, who remained within the boundaries of the Greek State after the exchange of populations under the Treaty of Lausanne, to the ECHR. The applicant, a Greek national of the Muslim minority of Western Thrace, complained that she could not be beneficiary by testament of her deceased husband’s estate, member of the same minority, since, according to the position of the Court of Cassation, due to a series of international agreements and relevant domestic norms, the law of succession applicable to her case was the Islamic Law that prohibits the testament, instead of the civil law. However, the ECtHR found that the applicant was victim of a violation of article 14 of the ECHR in conjunction with article 1 of Protocol no 1. In this case, the ECtHR considered for the first time the question of the compatibility of a religious community’s separate legal status with the ECHR. The rationale behind the decision is within the framework of the core principles of the Court’s case law on the limits of the autonomy of religious communities and acknowledgement of minority rights. The Court, based on the main line of arguments which constitute the corpus of its jurisprudence on religious and minority issues, ruled that the separate legal status of the Muslim minority cannot justify divergences from the application of the General Law, to the extent that such divergences violate the Greek citizens’ rights enshrined in the Constitution and the ECHR and it condemned Greece on the basis of “discrimination by association”.
A Single Case Narrative of Spirituality Following Aphasia from Traumatic Brain Injury: Findings about Forgiveness and Freedom Using WELLHEAD and SHALOM
Authors: Mumby Katharyn
Published: May 2019

Rehabilitation has neglected the spirituality of people with aphasia, a neurogenic impairment of language for communication and thought processes. Aphasia reduces scope for adjustment processes where words are normal currency, such as forgiveness and reconciliation. A single case narrative was generated from a case series exploring the feasibility of spiritual health assessment in aphasia. The individual had traumatic brain injury, with the primary symptom of aphasia, giving the first detailed account of its kind. The WELLHEAD spirituality toolkit provided a structured interview approach, exploring spirituality in terms of ‘meaning and purpose’ within four dimensions, WIDE, LONG, HIGH and DEEP, incorporating patient-reported outcome measures and goal-setting, with feedback interviews. Spiritual Health and Life Orientation Measure (SHALOM) generated a comparator spiritual health assessment. The quantitative feedback measures and self-reported outcomes were complemented by detailed qualitative interview transcripts subject to systematic thematic analysis in NVivo. The findings were co-constructed and systematically verified. This non-religious narrative evidenced the accessibility, acceptability, and impact of the resources. Self-forgiveness was paramount for freedom to journey into the unknown beyond self with ‘Calm’, towards helping others and accepting help. Religion, Faith and Belief were reconceptualised. Forgiveness of self and others was integral and instrumental in recovery, offering avenues for further investigation and application.
The Aesthetic Face of the Sacred
Authors: Džalto Davor
Published: May 2019

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Travel as hicret: (Re)Framing Experiences of Exile in the Gülen Community in Brazil
Authors: Dumovich Liza
Published: May 2019

This article analyzes how members of the Gülen community in Brazil have mobilized the Islamic tradition in order to make reason of critical changes in their lives, since July 2016 failed coup in Turkey. This community is part of the Gülen Movement, a transnational Turkish Islamic network that operates mainly through educational and cultural activities. The Movement’s charismatic religious leader, Fethullah Gülen, was held responsible for the failed putsch and its participants have since been persecuted by the Turkish government both at home and abroad. The article shows how Gülen’s discursive articulation of the notions of hizmet (religious service) and hicret has been mobilized by his followers settled in Brazil as an Islamic framework that provides them with moral reasoning to carry on in what they define as the Prophet’s path. It also shows that changes in economic and political context may lead to different motivations and objectives in one’s trajectory, producing a reconfiguration of meanings related to travel, migration and diaspora.
Optimal Excess-of-Loss Reinsurance for Stochastic Factor Risk Models
Authors: Brachetta Matteo , Ceci Claudia
Published: May 2019

We study the optimal excess-of-loss reinsurance problem when both the intensity of the claims arrival process and the claim size distribution are influenced by an exogenous stochastic factor. We assume that the insurer’s surplus is governed by a marked point process with dual-predictable projection affected by an environmental factor and that the insurance company can borrow and invest money at a constant real-valued risk-free interest rate r. Our model allows for stochastic risk premia, which take into account risk fluctuations. Using stochastic control theory based on the Hamilton-Jacobi-Bellman equation, we analyze the optimal reinsurance strategy under the criterion of maximizing the expected exponential utility of the terminal wealth. A verification theorem for the value function in terms of classical solutions of a backward partial differential equation is provided. Finally, some numerical results are discussed.
Stackelberg Equilibrium Premium Strategies for Push-Pull Competition in a Non-Life Insurance Market with Product Differentiation
Authors: Asmussen Søren , Christensen Bent Jesper , Thøgersen Julie
Published: May 2019

Two insurance companies I 1 , I 2 with reserves R 1 ( t ) , R 2 ( t ) compete for customers, such that in a suitable differential game the smaller company I 2 with R 2 ( 0 ) < R 1 ( 0 ) aims at minimizing R 1 ( t ) − R 2 ( t ) by using the premium p 2 as control and the larger I 1 at maximizing by using p 1 . Deductibles K 1 , K 2 are fixed but may be different. If K 1 > K 2 and I 2 is the leader choosing its premium first, conditions for Stackelberg equilibrium are established. For gamma-distributed rates of claim arrivals, explicit equilibrium premiums are obtained, and shown to depend on the running reserve difference. The analysis is based on the diffusion approximation to a standard Cramér-Lundberg risk process extended to allow investment in a risk-free asset.
MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory
Authors: Guardeño Rafael , López Manuel J. , Sánchez Víctor M.
Published: May 2019

In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design method for multivariable PID controller is robust with respect to: (a) parametric uncertainty in the plant model, (b) disturbances acting at the plant input, (c) sensors measurement and estimation errors.
Research on Time-Correlated Errors Using Allan Variance in a Kalman Filter Applicable to Vector-Tracking-Based GNSS Software-Defined Receiver for Autonomous Ground Vehicle Navigation
Authors: Luo Yiran , Li Jian , Yu Chunyang , Xu Bing , Li You , Hsu Li-Ta , El-Sheimy Naser
Published: May 2019

The global navigation satellite system (GNSS) has been applied to many areas, e.g., the autonomous ground vehicle, unmanned aerial vehicle (UAV), precision agriculture, smart city, and the GNSS-reflectometry (GNSS-R), being of considerable significance over the past few decades. Unfortunately, the GNSS signal performance has the high risk of being reduced by the environmental interference. The vector tracking (VT) technique is promising to enhance the robustness in high dynamics as well as improve the sensitivity against the weak environment of the GNSS receiver. However, the time-correlated error coupled in the receiver clock estimations in terms of the VT loop can decrease the accuracy of the navigation solution. There are few works present dealing with this issue. In this work, the Allan variance is accordingly exploited to specify a model which is expected to account for this type of error based on the 1st-order Gauss-Markov (GM) process. Then, it is used for proposing an enhanced Kalman filter (KF) by which this error can be suppressed. Furthermore, the proposed system model makes use of the innovation sequence so that the process covariance matrix can be adaptively adjusted and updated. The field tests demonstrate the performance of the proposed adaptive vector-tracking time-correlated error suppressed Kalman filter (A-VTTCES-KF). When compared with the results produced by the ordinary adaptive KF algorithm in terms of the VT loop, the real-time kinematic (RTK) positioning and code-based differential global positioning system (DGPS) positioning accuracies have been improved by 14.17% and 9.73%, respectively. On the other hand, the RTK positioning performance has been increased by maximum 21.40% when compared with the results obtained from the commercial low-cost U-Blox receiver.
Estimating Wave Direction Using Terrestrial GNSS Reflectometry
Authors: Reinking Jörg , Roggenbuck Ole , Even-Tzur Gilad
Published: May 2019

The signal-to-noise ratio (SNR) data are part of the global navigation satellite systems (GNSS) observables. In a marine environment, the oscillation of the SNR data can be used to derive reflector heights. Since the attenuation of the SNR oscillation is related to the roughness of the sea surface, the significant wave height (SWH) of the water surface can be calculated from the analysis of the attenuation. The attenuation depends additionally on the relation between the coherent and the incoherent part of the scattered power. The latter is a function of the correlation length of the surface waves. Since the correlation length changes with respect to the direction of the line of sight relative to the wave direction, the attenuation must show an anisotropic characteristic. In this work, we present a method to derive the wave direction from the anisotropy of the attenuation of the SNR data. The method is investigated based on simulated data, as well by the analysis of experimental data from a GNSS station in the North Sea.
Ground-Based Radar Interferometry: A Bibliographic Review
Authors: Pieraccini Massimiliano , Miccinesi Lapo
Published: May 2019

Ground-based/terrestrial radar interferometry (GBRI) is a scientific topic of increasing interest in recent years. This article is a bibliographic review, as much complete as possible, of the scientific papers/articles published in the last 20 years, since the pioneering works in the nineties. Some statistics are reported here about the number of publications in the years, popularity of applications, operative modalities, operative bands. The aim of this review is also to identify directions and perspectives. In the opinion of authors, this type of radar systems will move forward faster modulations, wider view angle, MIMO (Multiple Input Multiple Output) systems and radar with capability to detect the vector of displacement and not only a single component.
Exploring the Influence of Spatial Resolution on the Digital Mapping of Soil Organic Carbon by Airborne Hyperspectral VNIR Imaging
Authors: Guo Long , Shi Tiezhu , Linderman Marc , Chen Yiyun , Zhang Haitao , Fu Peng
Published: May 2019

Accurate digital mapping of soil organic carbon (SOC) is important in understanding the global carbon cycle and its implications in mitigating climate change. Visible and near-infrared hyperspectral imaging technology provides an alternative for mapping SOC efficiently and accurately, especially at regional and global scales. However, there is a lack of understanding of the impacts of spatial resolution of hyperspectral images and spatial autocorrelation of spectral information on the accuracy of SOC retrievals. In this study, the hyperspectral images (380–1700 nm) with a spatial resolution of 1 m were acquired by Headwall Micro-Hyperspec airborne sensors. Then, hyperspectral images were resampled into three different spatial resolutions of 10 m, 30 m, and 60 m by near neighbor (NN), bilinear interpolation (BI), and cubic convolution (CC) resampling methods. The geographically weighted regression (GWR) model was used to explore the role of spatial autocorrelation in predicting SOC contrast with the partial least squares regression (PLSR) model. Results showed that (1) the hyperspectral images can be used to predict SOC and the spatial autocorrelation can improve the prediction accuracy, as the ratio of performance to interquartile range (RPIQ) values of PLSR and GWR were 1.957 and 2.003; (2) The SOC prediction accuracy decreased with the degradation of spatial resolution, and the RPIQ values of PLSR were from 1.957 to 1.134, and of GWR were from 2.003 to 1.136; (3) Three resampling methods had a much weaker influence than spatial resolution on SOC predictions because the differences of RPIQ values of NN, BI, and CC resampling methods were 0.146, 0.175, and 0.025 in the spatial resolutions of 10 m, 30 m, and 60 m, respectively; (4) Finally, the Global Moran’s I and the Anselin Local Moran’s I proved the existence of the spatial autocorrelation in SOC maps. We hope that this study can offer valuable information for digital soil mapping by satellite hyperspectral images in the near future.
S-RVoG Model Inversion Based on Time-Frequency Optimization for P-Band Polarimetric SAR Interferometry
Authors: Sun Xiaofan , Wang Bingnan , Xiang Maosheng , Fu Xikai , Zhou Liangjiang , Li Yinwei
Published: May 2019

This paper investigates the potential of the time-frequency optimization on the basis of the sublook decomposition for forest height estimation. The optimization is deemed to be capable of extracting a relatively accurate volume contribution when P-band polarimetric interferometric synthetic aperture radar (Pol-InSAR) systems are adopted to observe forest-covered areas. The highest and the lowest phase centers acquired by the time-frequency optimization modify the conventional three-stage inversion process. This paper presents, for the first time, a performance assessment of the time-frequency optimization on P-band Pol-InSAR data over boreal forests. Simultaneously, to alleviate the model inversion errors caused by topographic fluctuations, forest height is estimated based on the sloped Random Volume over Ground (S-RVoG) model in which the incidence angle is corrected with the terrain slope. The E-SAR P-band Pol-InSAR data acquired during the BIOSAR 2008 campaign in Northern Sweden is utilized to evaluate the performance of the proposed method. From the results of the forest height estimation preprocessed with time-frequency optimization, the root mean square error (RMSE) of Random Volume over Ground (RVoG) and S-RVoG model on negative slope are 5.09 m and 4.71 m, respectively. It is concluded that the time-frequency processing and negative terrain slope compensation improve the inversion performance by 41 . 49 % and 11 . 96 % , respectively.
Unmanned Aerial System Imagery, Land Data and User Needs: A Socio-Technical Assessment in Rwanda
Authors: Stöcker Claudia , Ho Serene , Nkerabigwi Placide , Schmidt Cornelia , Koeva Mila , Bennett Rohan , Zevenbergen Jaap
Published: May 2019

Unmanned Aerial Systems (UAS) are emerging as a tool for alternative land tenure data acquisition. Even though UAS appear to represent a promising technology, it remains unclear to what extent they match the needs of communities and governments in the land sector. This paper responds to this question by undertaking a socio-technical study in Rwanda, aiming to determine the match between stakeholders’ needs and the characteristics of the UAS data acquisition workflow and its final products as valuable spatial data for land administration and spatial planning. A needs assessment enabled the expression of a range of land information needs across multiple levels and stakeholder sectors. Next to the social study, three different UAS were flown to test not only the quality of data but the possibilities of the use of this technology within the current institutional environment. A priority list of needs for cadastral and non-cadastral information as well as insights into operational challenges and data quality measures of UAS-based data products are presented. It can be concluded that UAS can have a significant contribution to match most of the prioritized needs in Rwanda. However, the results also reveal that structural and capacity conditions currently undermine this potential.
Classification of PolSAR Image Using Neural Nonlocal Stacked Sparse Autoencoders with Virtual Adversarial Regularization
Authors: Wang Ruichuan , Wang Yanfei
Published: May 2019

Polarimetric synthetic aperture radar (PolSAR) has become increasingly popular in the past two decades, for it can derive multichannel features of ground objects, which contains more discriminative information compared with traditional SAR. In this paper, a neural nonlocal stacked sparse autoencoders with virtual adversarial regularization (NNSSAE-VAT) is proposed for PolSAR image classification. The NNSSAE first extracts the nonlocal features by calculating pairwise similarity of each pixel and its surrounding pixels using a neural network, which contains a multiscale feature extractor and a linear embedding layer. The feature extraction process can relieve the negative influence of speckle noise and extract discriminative nonlocal spatial information without carefully designed parameters. Then, the SSAE maps the center pixel and the extracted nonlocal features into deep latent space in which a Softmax classifier is utilized to conduct classification. The virtual adversarial training is introduced to regularize the network, which tries to keep the network from being overfitting. The experimental results from three real PolSAR image show that the proposed NNSSAE-VAT method has proved its robustness and effectiveness and it can achieve competitive performance compared with related methods.
A Collaborative Change Detection Approach on Multi-Sensor Spatial Imagery for Desert Wetland Monitoring after a Flash Flood in Southern Morocco
Authors: Hakdaoui Sofia , Emran Anas , Pradhan Biswajeet , Lee Chang-Wook , Nguemhe Fils Salomon Cesar
Published: May 2019

This study aims to present a technique that combines multi-sensor spatial data to monitor wetland areas after a flash-flood event in a Saharan arid region. To extract the most efficient information, seven satellite images (radar and optical) taken before and after the event were used. To achieve the objectives, this study used Sentinel-1 data to discriminate water body and soil roughness, and optical data to monitor the soil moisture after the event. The proposed method combines two approaches: one based on spectral processing, and the other based on categorical processing. The first step was to extract four spectral indices and utilize change vector analysis on multispectral diachronic images from three MSI Sentinel-2 images and two Landsat-8 OLI images acquired before and after the event. The second step was performed using pattern classification techniques, namely, linear classifiers based on support vector machines (SVM) with Gaussian kernels. The results of these two approaches were fused to generate a collaborative wetland change map. The application of co-registration and supervised classification based on textural and intensity information from Radar Sentinel-1 images taken before and after the event completes this work. The results obtained demonstrate the importance of the complementarity of multi-sensor images and a multi-approach methodology to better monitor changes to a wetland area after a flash-flood disaster.
A Cross-Chain Solution to Integrating Multiple Blockchains for IoT Data Management
Authors: Jiang Yiming , Wang Chenxu , Wang Yawei , Gao Lang
Published: May 2019

With the rapid development of the internet of things (IoT), traditional industries are setting off a massive wave of digitization. In the era of the Internet of Everything, millions of devices and links in IoT pose more significant challenges to data management. Most existing solutions employ centralized systems to control IoT devices, which brings about the privacy and security issues in IoT data management. Recently, blockchain has attracted much attention in the field of IoT due to its decentralization, traceability, and non-tamperability. However, it is non-trivial to apply the current blockchain techniques to IoT due to the lack of scalability and high resource costs. Different blockchain platforms have their particular advantages in the scenario of IoT data management. In this paper, we propose a cross-chain framework to integrate multiple blockchains for efficient and secure IoT data management. Our solution builds an interactive decentralized access model which employs a consortium blockchain as the control station. Other blockchain platforms customized for specific IoT scenarios run as the backbone of all IoT devices. It is equivalent to opening the off-chain channels on the consortium blockchain. Our model merges transactions in these channels for confirmation based on the notary mechanism. Finally, we implement a prototype of the proposed model based on hyperledge Fabric and IOTA Tangle. We evaluate the performance of our method through extensive experiments. The results demonstrate the effectiveness and efficiency of our framework.
Design and Implementation of Cloud Analytics-Assisted Smart Power Meters Considering Advanced Artificial Intelligence as Edge Analytics in Demand-Side Management for Smart Homes
Authors: Chen Yung-Yao , Lin Yu-Hsiu , Kung Chia-Ching , Chung Ming-Han , Yen I-Hsuan
Published: May 2019

In a smart home linked to a smart grid (SG), demand-side management (DSM) has the potential to reduce electricity costs and carbon/chlorofluorocarbon emissions, which are associated with electricity used in today’s modern society. To meet continuously increasing electrical energy demands requested from downstream sectors in an SG, energy management systems (EMS), developed with paradigms of artificial intelligence (AI) across Internet of things (IoT) and conducted in fields of interest, monitor, manage, and analyze industrial, commercial, and residential electrical appliances efficiently in response to demand response (DR) signals as DSM. Usually, a DSM service provided by utilities for consumers in an SG is based on cloud-centered data science analytics. However, such cloud-centered data science analytics service involved for DSM is mostly far away from on-site IoT end devices, such as DR switches/power meters/smart meters, which is usually unacceptable for latency-sensitive user-centric IoT applications in DSM. This implies that, for instance, IoT end devices deployed on-site for latency-sensitive user-centric IoT applications in DSM should be aware of immediately analytical, interpretable, and real-time actionable data insights processed on and identified by IoT end devices at IoT sources. Therefore, this work designs and implements a smart edge analytics-empowered power meter prototype considering advanced AI in DSM for smart homes. The prototype in this work works in a cloud analytics-assisted electrical EMS architecture, which is designed and implemented as edge analytics in the architecture described and developed toward a next-generation smart sensing infrastructure for smart homes. Two different types of AI deployed on-site on the prototype are conducted for DSM and compared in this work. The experimentation reported in this work shows the architecture described with the prototype in this work is feasible and workable.
Identifying Safety Training Resource Needs in the Cattle Feeding Industry in the Midwestern United States
Authors: Ramos Athena , Duysen Ellen , Yoder Aaron
Published: May 2019

Cattle feedyards are a high-risk environment. They are characterized by high rates of occupational injuries and illnesses. As such, there is a clear need to address the health and safety of cattle feedyard workers. Therefore, the purpose of this cross-sectional study was to explore safety training practices and preferences in the cattle feeding industry. A survey of feedyard managers, feedyard safety trainers, and feedyard operators was conducted (n = 28). We found that only half of respondents had dedicated safety personnel; however, there was interest in a safety training program, conducted through short hands-on and in-person methods with materials available in English and Spanish. The majority of participants were also interested in a feedyard safety certification program. Participants reaffirmed the importance of partnering with industry and other stakeholders when conducting these types of programs. The results of this Phase 1-type translational research study will be used to guide the development of feedyard safety trainings and a corresponding recognition program for feedyards and feedyard workers as part of the “Improving Safety and Health of Cattle Feedyard Workers” project.
Application of Sustainability Principles for Harsh Environment Exploration by Autonomous Robot
Authors: Bausys Romualdas , Cavallaro Fausto , Semenas Rokas
Published: May 2019

Currently, the European Union (EU) is focusing on a large-scale campaign dedicated to developing a competitive circular economy and expanding the single digital market. One of the main goals of this campaign is the implementation of the sustainability principles in the development and deployment cycle of the new generation technologies. This paper focuses on the fast-growing field of autonomous mobile robots and the harsh environment exploration problem. Currently, most state-of-the-art navigation methods are utilising the idea of evaluating candidate observation locations by combining different task-related criteria. However, these map building solutions are often designed for operating in near-perfect environments, neglecting such factors as the danger to the robot. In this paper, a new strategy that aims to address the safety and re-usability of the autonomous mobile agent by implementing the economic sustainability principles is proposed. A novel multi-criteria decision-making method of Weighted Aggregated Sum Product Assessment—Single-Valued Neutrosophic Sets, namely WASPAS-SVNS, and the weight selection method of Step-Wise Weights Assessment Ratio Analysis (SWARA) are applied to model a dynamic decision-making system. The experimental evaluation of the proposed strategy shows that increased survivability of the autonomous agent can be observed. Compared to the greedy baseline strategy, the proposed method forms the movement path which orients the autonomous agent away from dangerous obstacles.
Coupling a Building Energy Simulation Tool with a Microclimate Model to Assess the Impact of Cool Pavements on the Building’s Energy Performance Application in a Dense Residential Area
Authors: Tsoka Stella , Tsikaloudaki Katerina , Theodosiou Theodoros
Published: May 2019

Replacing conventional pavements with the corresponding high albedo ones constitutes a well-known technique to improve outdoor thermal environment of modern cites. Since most of the existing studies assess the impact of the high albedo pavements at the pedestrian’s height and with respect to thermal comfort, this study aims to examine the effect of the application of highly reflective pavements on the heating and cooling energy needs of a building unit, located inside a dense urban area. Aiming at a higher accuracy of the energy performance simulations, an integrated computational method between ENVI-met model, Meteonorm weather data generator and Energy Plus software is established, to consider the site-specific microclimatic characteristics of the urban areas. The analysis is performed both for the design and the aged albedo values as significant changes may occur due to aging process. The analysis revealed that the application of cool materials on the ground surfaces only marginally affects the energy performance of the examined building unit, both for the design and the aged albedo value; changes on the annual heating and cooling energy demand, for both albedo scenarios did not exceed 1.5% revealing the limited potential of cool pavements regarding the improvement of the energy performance of urban building units.
Influence of Ripening on Chemical Characteristics of a Traditional Italian Cheese: Provolone del Monaco
Authors: Manzo Nadia , Santini Antonello , Pizzolongo Fabiana , Aiello Alessandra , Marrazzo Andrea , Meca Giuseppe , Durazzo Alessandra , Lucarini Massimo , Romano Raffaele
Published: May 2019

The envisaged promotion of local products contributes to environmental protection and is a valid tool for the promotion of socioeconomic development, enhancement of territories, and biodiversity preservation and sustainability. Provolone del Monaco is a semi hard pasta filata cheese granted PDO (Protected Designation of Origin) designation by the European Union. Provolone del Monaco is obtained from raw cow’s milk, produced in the specific areas of the Lattari Mountains and Sorrento Peninsula (Naples, Italy), and ripened for at least six months. To the best of our knowledge, no studies concerning the complete chemical characterization of Provolone del Monaco cheese are available. In the present study; the chemical characterization (moisture; pH; titratable acidity; nitrogen; and fat content), fatty acid composition determined by using gas-chromatography-flame-ionization-detector (GC-FID); volatile organic compounds by solid-phase microextraction followed by gas chromatography-mass spectrometry (SPME-GC/MS), and maturation indices were evaluated during ripening. Two different average typical cheese sizes (3 kg and 5 kg) and two different internal portions were studied. After 6 months of ripening, the most important changes recorded were the loss of water, the increase in acidity, the nitrogen (as ammonia) release, and the production of volatile organic compounds. The cheese size did not affect the chemical composition of Provolone del Monaco.
Efforts toward Creating a Sustainable Business Model: An Empirical Investigation of Small-Scale Certified Forestry Firms in Taiwan
Authors: Lee Jun-Yen , Chang Ching-Hsing
Published: May 2019

Forest certification plays a notable role in promoting sustainability. This certification shows that forestland holders have adopted innovative practices toward realizing sustainable business models. Relatively little analysis has been devoted to identifying the efforts of transforming a conventional business model into a sustainable version through the application of forest certification. This paper examines the elements of a sustainable business model: value proposition, value creation and delivery, and value capture in certified forestland holders’ business operations. Empirical results have confirmed that certification signifies a successful sustainability transformation within adopting firms. However, these small organizations struggle with obtaining know-how regarding sustainable forest management. There needs to be adequate external support, such as government consultants or academic researchers, in order to successfully adopt third-party forest certification. However, while practicing sustainable forest management activities will not guarantee premium prices, the certification has, in some rare cases, helped to develop a new niche market. Good communication with stakeholders has improved firms’ relationships with local residents, but more channels of communication are still needed to activate green consumers.
The Sustainable Development of Financial Inclusion: How Can Monetary Policy and Economic Fundamental Interact with It Effectively?
Authors: Yin Xuluo , Xu Xuan , Chen Qi , Peng Jiangang
Published: May 2019

It is necessary to analyze the relationship between financial inclusion and circumstances-monetary policy and economic fundamentals, which has a practical reference value for policy makers. This paper studies the impact of the circumstances on financial inclusion factors by using a vector autoregressive method. Empirical results show that monetary policy has a short-term positive impact on financial inclusion factors, while the economic fundamental has the opposite, which means that the positive monetary policy promote the development of financial inclusion in the short term and the sudden change of the economic situation will make it harder. Based on the data of the World Bank and the situation of China, we make an analysis and comparison of the empirical results, and draw two implications: first, the sustainable development of financial inclusion needs a suitable circumstance; second, the appropriate coordination and mutual facilitation of economic fundamentals and finance is conducive to the sustainable development of financial inclusion.
Developing and Validating a Theory-Based Model of Crowdfunding Investment Intention—Perspectives from Social Exchange Theory and Customer Value Perspective
Authors: Yang Xiaocong , Zhao Kai , Tao Xiaobo , Shiu Eric
Published: May 2019

In order to improve public financing sustainability in China, the Chinese government has announced several administrative policies on crowdfunding, concerning platform construction and operation, in recent years. However, the existing policy scope rarely mentions the importance of social psychology, which also plays a decisive role in determining the participation and success rates of crowdfunding. Therefore, this study uses the knowledge from social exchange theory (SET) and customer value perspective (CVP) to develop and validate a conceptual model of the key determinants of the public’s intention in investing in crowdfunded projects in China. Based on the primary survey data, the SEM (structural equation modeling) estimations suggest that: (1) communication, shared values, investors’ perceived benefits, and perceived risk have significant effects on crowdfunding investors’ trust in fundraisers of a particular crowdfunding project, which in turn act on their commitment and intentions to invest in the project; (2) trust strengthens funding intentions through fulfilling commitments, whereas its direct effect on funding intentions is insignificant; (3) commitment has a direct and significant positive effect on the enhancement of funding intentions. These findings propose a new perspective of improving public policies to support small and micro enterprises (SMEs) and individual innovative projects in China.
Analysis of the Concept of Energy in the Spanish Curriculum of Secondary Education and Baccalaureate: A Sustainable Perspective
Authors: Martínez-Borreguero Guadalupe , Maestre-Jiménez Jesús , Naranjo-Correa Francisco Luis , Mateos-Núñez Milagros
Published: May 2019

Teaching and learning of concepts within the science, technology, society, and environment (STSE) approach, such as energy, are key elements in improving students’ competencies in sustainability within the framework of environmental education. The overall objective of this research has been to analyze the concept of energy in secondary education curriculum from a sustainable perspective. Likewise, the levels of cognitive demand in the curriculum for the students’ acquisition of the concept are analyzed. The design of the research is a descriptive, exploratory type, with mixed qualitative and quantitative analysis of the obtained data. A methodology similar to that carried out in other researches was followed, and an analysis established a system of categories to classify the references found. The results obtained reveal that the regulations that govern teaching of secondary education (12–18 years) deal in depth, and in an compulsory way, with the concept of energy. However, more action is required to promote sustainability at all stages of education, in order to alleviate current and future environmental problems.
Performance Evaluation of the Implementation of the 2013/34/EU Directive in Romania on the Basis of Corporate Social Responsibility Reports
Authors: Gh. Popescu Cristina Raluca , Banța Viorel Costin
Published: May 2019

The paper highlights part of the results of an investigation-based analysis. The research was carried out at the level of the 680 public interest entities with over 500 employees, for the first time enforced by law, together with the financial statements for 2017 reported in 2018, to publish non-financial social responsibility, the environment, and promotion of an ethical and sustainable business with sufficient and measurable care for the employees, the environment, and the local community. The analysis was extended to a representative sample of 246 entities, for which we analyzed both the degree of compliance of entities in Romania with their obligation to make non-financial information public and the determination of the level of compliance of the content of non-financial reports in depending on the minimum requirements of the directive. Thus, the most common published non-financial information has been identified, which has allowed for the definition of a sustainable and competitive business. The degree of compliance was also determined at the territorial, structural, and legal level. Moreover, this scientific study emphasizes the strong connections that exist between key concepts, such as: corporate social responsibility, intellectual capital, environmental protection, sustainability, ethics and integrity in today’s contemporary society.
Perceived Barriers to Implementing Education for Sustainable Development among Korean Teachers
Authors: Kang Woonsun
Published: May 2019

The objective of this study was to identify whether there are any homogeneous subclasses of teachers exhibiting different profiles of barriers to implementing ESD among Korean secondary teachers, and to examine whether teachers’ experiences of taking an ESD course in their pre-service teacher education and in their in-service training on ESD are predictive of membership in subclasses of perceived barriers to implementing ESD. Korean secondary teachers from various subjects were selected as a sample. I carried out latent class analysis (LCA) on barrier variables and assessed the association of both the experiences of taking an ESD course in their pre-service teacher education and in-service training on ESD with membership in the latent subclasses using multi-nominal logistic regression. These analyses were performed using PROC LCA. Research results are as follows: Firstly, four latent classes were identified: the few barrier, the individual barrier, the combination of individual and class-driven structural barrier, and the combination of individual and structural barrier. Secondly, both the experiences of taking an ESD course in their pre-service teacher education and in-service training on ESD were significant predictors of latent class membership. The current study could potentially assist both pre-service teacher educational institutions and in-service teacher training organizations with strategies designed to improve ESD competency among teachers.
How Does Consumers’ Omnichannel Shopping Behaviour Translate into Travel and Transport Impacts? Case-Study of a Footwear Retailer in Belgium
Authors: Buldeo Rai Heleen , Mommens Koen , Verlinde Sara , Macharis Cathy
Published: May 2019

Retailers and consumers are increasingly “omnichannel”. This means that retailers offer multiple integrated offline and online channels to their customers, while consumers use multiple offline and online channels throughout their shopping journeys. In these shopping journeys, consumers can travel for researching, testing, receiving and returning activities related to a purchase, next to the purchasing itself. It is unclear how such omnichannel consumer behaviour materialises in practice. This information is important for practitioners from retail as well as for society, not in the least because of the environmental impact that shopping trips generate. Existing environmental assessments of retail-related transport and logistics do not account for consumers’ omnichannel shopping and travel behaviour. To fill this gap in research, we set up a case-study collaboration with an omnichannel footwear retailer in Belgium. We collected data on logistics and consumer flows and analysed this data to determine the CO2 footprint. Our research results in six profiles, of which “the online shopper” that shops online and receives its purchase at home or at a collection point generates the lowest impact. However, when online shoppers travel to stores prior to their e-purchase and become “showroomers”, the external CO2 costs double compared to “traditional shoppers” that carry out all shopping activities in-store and are more than eight times higher compared to “online shoppers”. Although the case-study context should be taken into account (e.g., in terms of product type, retailer type and geography), a sensitivity analysis demonstrates the robustness of our results.
Does the Development of Information and Communication Technology and Transportation Infrastructure Affect China’s Educational Inequality?
Authors: Zhou Peng , Chen Fengwen , Wang Wei , Song Peixin , Zhu Chenliang
Published: May 2019

Educational inequality is an important factor in the development of human capital, and limits the output of regional economic activities. The unequal distribution of educational resources has become a hot topic noticed by the public, and has restricted sustainable economic growth. This paper provides a better understanding of educational inequality, and explores the impacts of information and communication technology (ICT) and transportation infrastructure on the distribution of educational resources. The panel data models are constructed to discuss the relationship among ICT, transportation infrastructure, and educational inequality, using the data of 31 provinces in China from 2006 to 2016. The empirical results show that there is a positive relationship between ICT and educational inequality, while transportation infrastructure can restrain the unequal distribution of educational resources. Moreover, there is a significant inverted U-shaped relationship between transportation infrastructure and educational inequality. Since China’s education reform in 2010, the relationship among ICT, transportation infrastructure, and educational inequality has been significantly changed, as well as the influence mechanism of ICT. In addition, transportation infrastructure in China western regions can effectively alleviate the problem of educational inequality, and its impact will increase with the growth of transportation investments. It is necessary to consider the rational allocation of educational resources, and this is essential to relieve the problem of educational inequality. Therefore, our results demonstrate the key roles of information technology and transportation network in the field of education, and provide some new ideas for the solution of educational inequality.
The Influence of Viewing Photos of Different Types of Rural Landscapes on Stress in Beijing
Authors: Wang Xiaobo , Zhu Hanlun , Shang Zhendong , Chiang Yencheng
Published: May 2019

The environment can affect people’s health by relieving stress, and rural landscape as a special environment might influence human’s stress relief. This study takes different types of rural landscapes as the research object to explore their impact on stress levels, which are shown by photos. As an independent variable, the rural landscape is divided into three levels: Type 1 (natural landscape), type 2 (productive landscape), and type 3 (artificial landscape). Seventy-three subjects were randomly assigned to each type of rural landscape. Salivary cortisol, blood pressure, heart rate, and a subjective rating state scale (brief profile of mood states, BPOMS) were used as indicators of stress. At the same time, the influence of preference and familiarity on the stress relieving effect was also discussed. A paired t-test and one-way analysis of variance (ANOVA) were used as the main statistical methods. In the results of t-test for pre-posttest, significant difference was observed in high blood pressure, heart rate, and total mood disturbance (TMD) of type 1 and type 2, and the high and low blood pressure of type 3; ANOVA analysis revealed that for the difference of pre-posttest, significant difference was observed in the TMD value among the three types; except for type 3, blood pressure, heart rate, and BPOMS values were significantly affected by preference and familiarity. The conclusions include the following: The three types of rural landscapes have a positive effect on relieving stress; the productive landscape has the best effect on relieving stress; and users’ landscape preferences and familiarity with the environment can affect the effect of stress relief in rural landscapes.