bluuebunny/crossref_metadata_2025 huggingface dataset:
An Overview of Recent Advances in State-of-the-Art Techniques in the Demulsification of Crude Oil Emulsions
Authors: Saad M. A. , Kamil Mohammed , Abdurahman N. H. , Yunus Rosli Mohd , Awad Omar I.
Published: July 2019

The processing of crude oil often requires the extraction of a large amount of water. Frequently, crude oil is mixed with water to form water-in-crude oil emulsions as the result of factors such as high shear at the production wellhead and surface-active substances that are naturally present in crude oil. These emulsions are undesirable and require demulsification to remove the dispersed water and associated inorganic salts in order to meet production and transportation specifications. Additionally, the demulsification of these crude oil emulsions mitigates corrosion and catalyst poisoning and invariably maximizes the overall profitability of crude oil production. Recently, there has been growing research interest in developing workable solutions to the difficulties associated with transporting and refining crude oil emulsions and the restrictions on produced water discharge. Therefore, this paper reviews the recent research efforts on state-of-the-art demulsification techniques. First, an overview of crude oil emulsion types, formation, and stability is presented. Then, the parameters and mechanisms of emulsification formation and different demulsification techniques are extensively examined. It is worth noting that the efficiency of each of these techniques is dependent on the operating parameters and their interplay. Moreover, a more effective demulsification process could be attained by leveraging synergistic effects by combining one or more of these techniques. Finally, this literature review then culminates with propositions for future research. Therefore, the findings of this study can help for a better understanding of the formation and mechanisms of the various demulsification methods of crude oil to work on the development of green demulsifiers by different sources.
Choline-Based Ionic Liquids as Media for the Growth of Saccharomyces cerevisiae
Authors: Sivapragasam Magaret , Wilfred Cecilia Devi , Jaganathan Joshua Raj , Krishnan Sooridarsan , Ab Wan Karim Ghani Wan Azlina Wan
Published: July 2019

Ionic liquids (ILs) have garnered great attention as alternative solvents in many biological reactions and applications. However, its unknown toxicity is in line with the challenges to use it for biological applications. In this study, three choline based Ionic Liquids—choline saccharinate (CS), choline dihydrogen phosphate (CDHP), and choline tryptophanate (CT) were assessed for their suitability on the growth of Saccharomyces cerevisiae. The ILs were incorporated into the growth media of S. cerevisiae (defined as synthetic media) to access its potential as a substitute to conventional media. The compatibility of the synthetic media was evaluated based on the toxicity (EC50), growth curve, and glucose profile. The results showed that the incorporation of CDHP and CS did promote the growth of S. cerevisiae with a rapid glucose consumption rate. The growth of S. cerevisiae with the media composition of yeast extract, peptone, and CS showed improvement of 13%. We believe that these observations have implications in the biocompatibility studies of ILs to microorganisms.
Temporal Feature Selection for Multi-Step Ahead Reheater Temperature Prediction
Authors: Gui Ning , Lou Jieli , Qiu Zhifeng , Gui Weihua
Published: July 2019

Accurately predicting the reheater steam temperature over both short and medium time periods is crucial for the efficiency and safety of operations. With regard to the diverse temporal effects of influential factors, the accurate identification of delay orders allows effective temperature predictions for the reheater system. In this paper, a deep neural network (DNN) and a genetic algorithm (GA)-based optimal multi-step temporal feature selection model for reheater temperature is proposed. In the proposed model, DNN is used to establish a steam temperature predictor for future time steps, and GA is used to find the optimal delay orders, while fully considering the balance between modeling accuracy and computational complexity. The experimental results for two ultra-super-critical 1000 MW power plants show that the optimal delay orders calculated using this method achieve high forecasting accuracy and low computational overhead. Moreover, it is argued that the similarities of the two reheater experiments reflect the common physical properties of different reheaters, so the proposed algorithms could be generalized to guide temporal feature selection for other reheaters.
Solution to the Time-Dependent Coupled Harmonic Oscillators Hamiltonian with Arbitrary Interactions
Authors: Urzúa Alejandro R. , Ramos-Prieto Irán , Fernández-Guasti Manuel , Moya-Cessa Héctor M.
Published: July 2019

We show that by using the quantum orthogonal functions invariant, we found a solution to coupled time-dependent harmonic oscillators where all the time-dependent frequencies are arbitrary. This system may be found in many applications such as nonlinear and quantum physics, biophysics, molecular chemistry, and cosmology. We solve the time-dependent coupled harmonic oscillators by transforming the Hamiltonian of the interaction using a set of unitary operators. In passing, we show that N time-dependent and coupled oscillators have a generalized orthogonal functions invariant from which we can write a Ermakov–Lewis invariant.
Editorial for the Special Issue “Frontiers in Spectral Imaging and 3D Technologies for Geospatial Solutions”
Authors: Honkavaara Eija , Karantzalos Konstantinos , Liang Xinlian , Nocerino Erica , Pölönen Ilkka , Rönnholm Petri
Published: July 2019

This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was used in object analysis.
Using Solar-Induced Chlorophyll Fluorescence Observed by OCO-2 to Predict Autumn Crop Production in China
Authors: Wei Jin , Tang Xuguang , Gu Qing , Wang Min , Ma Mingguo , Han Xujun
Published: July 2019

The remote sensing of solar-induced chlorophyll fluorescence (SIF) has attracted considerable attention as a new monitor of vegetation photosynthesis. Previous studies have revealed the close correlation between SIF and terrestrial gross primary productivity (GPP), and have used SIF to estimate vegetation GPP. This study investigated the relationship between the Orbiting Carbon Observatory-2 (OCO-2) SIF products at two retrieval bands (SIF757, SIF771) and the autumn crop production in China during the summer of 2015 on different timescales. Subsequently, we evaluated the performance to estimate the autumn crop production of 2016 by using the optimal model developed in 2015. In addition, the OCO-2 SIF was compared with the moderate resolution imaging spectroradiometer (MODIS) vegetation indices (VIs) (normalized difference vegetation index, NDVI; enhanced vegetation index, EVI) for predicting the crop production. All the remotely sensed products exhibited the strongest correlation with autumn crop production in July. The OCO-2 SIF757 estimated autumn crop production best (R2 = 0.678, p < 0.01; RMSE = 748.901 ten kilotons; MAE = 567.629 ten kilotons). SIF monitored the crop dynamics better than VIs, although the performances of VIs were similar to SIF. The estimation accuracy was limited by the spatial resolution and discreteness of the OCO-2 SIF products. Our findings demonstrate that SIF is a feasible approach for the crop production estimation and is not inferior to VIs, and suggest that accurate autumn crop production forecasts while using the SIF-based model can be obtained one to two months before the harvest. Furthermore, the proposed method can be widely applied with the development of satellite-based SIF observation technology.
Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification
Authors: Mi Jiaxin , Yang Yongjun , Zhang Shaoliang , An Shi , Hou Huping , Hua Yifei , Chen Fuyao
Published: July 2019

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.
Canopy and Terrain Height Retrievals with ICESat-2: A First Look
Authors: Neuenschwander Amy L. , Magruder Lori A.
Published: July 2019

NASA’s Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) launched in fall 2018 and has since collected continuous elevation data over the Earth’s surface. The primary scientific objective is to measure the cryosphere for studies related to land ice and sea ice characteristics. The vantage point from space, however, provides the opportunity to measure global surfaces including oceans, land, and vegetation. The ICESat-2 mission has dedicated products to the represented surface types, including an along-track elevation profile of terrain and canopy heights (ATL08). This study presents the first look at the ATL08 product and the quantitative assessment of the canopy and terrain height retrievals as compared to airborne lidar data. The study also provides qualitative examples of ICESat-2 observations from selected ecosystems to highlight the broad capability of the satellite for vegetation applications. Analysis of the mission’s preliminary ATL08 data product accuracy using an ICESat-2 transect over a vegetated region of Finland indicates a 5 m offset in geolocation knowledge (horizontal accuracy) well within the 6.5 m mission requirement. The vertical RMSE for the terrain and canopy height retrievals for one transect are 0.85 m and 3.2 m respectively.
Evaluating the Variability of Urban Land Surface Temperatures Using Drone Observations
Authors: Naughton Joseph , McDonald Walter
Published: July 2019

Urbanization and climate change are driving increases in urban land surface temperatures that pose a threat to human and environmental health. To address this challenge, we must be able to observe land surface temperatures within spatially complex urban environments. However, many existing remote sensing studies are based upon satellite or aerial imagery that capture temperature at coarse resolutions that fail to capture the spatial complexities of urban land surfaces that can change at a sub-meter resolution. This study seeks to fill this gap by evaluating the spatial variability of land surface temperatures through drone thermal imagery captured at high-resolutions (13 cm). In this study, flights were conducted using a quadcopter drone and thermal camera at two case study locations in Milwaukee, Wisconsin and El Paso, Texas. Results indicate that land use types exhibit significant variability in their surface temperatures (3.9–15.8 °C) and that this variability is influenced by surface material properties, traffic, weather and urban geometry. Air temperature and solar radiation were statistically significant predictors of land surface temperature (R2 0.37–0.84) but the predictive power of the models was lower for land use types that were heavily impacted by pedestrian or vehicular traffic. The findings from this study ultimately elucidate factors that contribute to land surface temperature variability in the urban environment, which can be applied to develop better temperature mitigation practices to protect human and environmental health.
Deep Fully Convolutional Networks for Cadastral Boundary Detection from UAV Images
Authors: Xia Xue , Persello Claudio , Koeva Mila
Published: July 2019

There is a growing demand for cheap and fast cadastral mapping methods to face the challenge of 70% global unregistered land rights. As traditional on-site field surveying is time-consuming and labor intensive, imagery-based cadastral mapping has in recent years been advocated by fit-for-purpose (FFP) land administration. However, owing to the semantic gap between the high-level cadastral boundary concept and low-level visual cues in the imagery, improving the accuracy of automatic boundary delineation remains a major challenge. In this research, we use imageries acquired by Unmanned Aerial Vehicles (UAV) to explore the potential of deep Fully Convolutional Networks (FCNs) for cadastral boundary detection in urban and semi-urban areas. We test the performance of FCNs against other state-of-the-art techniques, including Multi-Resolution Segmentation (MRS) and Globalized Probability of Boundary (gPb) in two case study sites in Rwanda. Experimental results show that FCNs outperformed MRS and gPb in both study areas and achieved an average accuracy of 0.79 in precision, 0.37 in recall and 0.50 in F-score. In conclusion, FCNs are able to effectively extract cadastral boundaries, especially when a large proportion of cadastral boundaries are visible. This automated method could minimize manual digitization and reduce field work, thus facilitating the current cadastral mapping and updating practices.
Automatic Building Outline Extraction from ALS Point Clouds by Ordered Points Aided Hough Transform
Authors: Widyaningrum Elyta , Gorte Ben , Lindenbergh Roderik
Published: July 2019

Many urban applications require building polygons as input. However, manual extraction from point cloud data is time- and labor-intensive. Hough transform is a well-known procedure to extract line features. Unfortunately, current Hough-based approaches lack flexibility to effectively extract outlines from arbitrary buildings. We found that available point order information is actually never used. Using ordered building edge points allows us to present a novel ordered points–aided Hough Transform (OHT) for extracting high quality building outlines from an airborne LiDAR point cloud. First, a Hough accumulator matrix is constructed based on a voting scheme in parametric line space (θ, r). The variance of angles in each column is used to determine dominant building directions. We propose a hierarchical filtering and clustering approach to obtain accurate line based on detected hotspots and ordered points. An Ordered Point List matrix consisting of ordered building edge points enables the detection of line segments of arbitrary direction, resulting in high-quality building roof polygons. We tested our method on three different datasets of different characteristics: one new dataset in Makassar, Indonesia, and two benchmark datasets in Vaihingen, Germany. To the best of our knowledge, our algorithm is the first Hough method that is highly adaptable since it works for buildings with edges of different lengths and arbitrary relative orientations. The results prove that our method delivers high completeness (between 90.1% and 96.4%) and correctness percentages (all over 96%). The positional accuracy of the building corners is between 0.2–0.57 m RMSE. The quality rate (89.6%) for the Vaihingen-B benchmark outperforms all existing state of the art methods. Other solutions for the challenging Vaihingen-A dataset are not yet available, while we achieve a quality score of 93.2%. Results with arbitrary directions are demonstrated on the complex buildings around the EYE museum in Amsterdam.
A New Approach to Earth’s Gravity Field Modeling Using GPS-Derived Kinematic Orbits and Baselines
Authors: Guo Xiang , Zhao Qile
Published: July 2019

Earth’s gravity field recovery from GPS observations collected by low earth orbiting (LEO) satellites is a well-established technique, and kinematic orbits are commonly used for that purpose. Nowadays, more and more satellites are flying in close formations. The GPS-derived kinematic baselines between them can reach millimeter precision, which is more precise than the centimeter-level kinematic orbits. Thus, it has long been expected that the more precise kinematic baselines can deliver better gravity field solutions. However, this expectation has not been met yet in practice. In this study, we propose a new approach to gravity field modeling, in which kinematic orbits of the reference satellite and baseline vectors between the reference satellite and its accompanying satellite are jointly inverted. To validate the added value, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used. We derive kinematic orbits and inter-satellite baselines of the twin GRACE satellites from the GPS data collected in the year of 2010. Then two sets of monthly gravity field solutions up to degree and order 60 are produced. One is derived from kinematic orbits of the twin GRACE satellites (‘orbit approach’). The other is derived from kinematic orbits of GRACE A and baseline vectors between GRACE A and B (‘baseline approach’). Analysis of observation postfit residuals shows that noise in the kinematic baselines is notably lower than the kinematic orbits by 50, 47 and 43% for the along-track, cross-track and radial components, respectively. Regarding the gravity field solutions, analysis in the spectral domain shows that noise of the gravity field solutions beyond degree 10 can be significantly reduced when the baseline approach is applied, with cumulative errors up to degree 60 being reduced by 34%, when compared to the orbit approach. In the spatial domain, the recovered mass changes with the baseline approach are more consistent with those inferred from the K-Band Ranging based solutions. Our results demonstrate that the proposed baseline approach is able to provide better gravity field solutions than the orbit approach. The findings may facilitate, among others, bridging the gap between GRACE and GRACE Follow-On satellite mission.
Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions
Authors: Runge Alexandra , Grosse Guido
Published: July 2019

The Arctic-Boreal regions experience strong changes of air temperature and precipitation regimes, which affect the thermal state of the permafrost. This results in widespread permafrost-thaw disturbances, some unfolding slowly and over long periods, others occurring rapidly and abruptly. Despite optical remote sensing offering a variety of techniques to assess and monitor landscape changes, a persistent cloud cover decreases the amount of usable images considerably. However, combining data from multiple platforms promises to increase the number of images drastically. We therefore assess the comparability of Landsat-8 and Sentinel-2 imagery and the possibility to use both Landsat and Sentinel-2 images together in time series analyses, achieving a temporally-dense data coverage in Arctic-Boreal regions. We determined overlapping same-day acquisitions of Landsat-8 and Sentinel-2 images for three representative study sites in Eastern Siberia. We then compared the Landsat-8 and Sentinel-2 pixel-pairs, downscaled to 60 m, of corresponding bands and derived the ordinary least squares regression for every band combination. The acquired coefficients were used for spectral bandpass adjustment between the two sensors. The spectral band comparisons showed an overall good fit between Landsat-8 and Sentinel-2 images already. The ordinary least squares regression analyses underline the generally good spectral fit with intercept values between 0.0031 and 0.056 and slope values between 0.531 and 0.877. A spectral comparison after spectral bandpass adjustment of Sentinel-2 values to Landsat-8 shows a nearly perfect alignment between the same-day images. The spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to Landsat-8 very well in Eastern Siberian Arctic-Boreal landscapes. After spectral adjustment, Landsat and Sentinel-2 data can be used to create temporally-dense time series and be applied to assess permafrost landscape changes in Eastern Siberia. Remaining differences between the sensors can be attributed to several factors including heterogeneous terrain, poor cloud and cloud shadow masking, and mixed pixels.
Revealing Kunming’s (China) Historical Urban Planning Policies Through Local Climate Zones
Authors: Vandamme Stéphanie , Demuzere Matthias , Verdonck Marie-Leen , Zhang Zhiming , Van Coillie Frieke
Published: July 2019

Over the last decade, Kunming has been subject to a strong urbanisation driven by rapid economic growth and socio-economic, topographical and proximity factors. As this urbanisation is expected to continue in the future, it is important to understand its environmental impacts and the role that spatial planning strategies and urbanisation regulations can play herein. This is addressed by (1) quantifying the cities’ expansion and intra-urban restructuring using Local Climate Zones (LCZs) for three periods in time (2005, 2011 and 2017) based on the World Urban Database and Access Portal Tool (WUDAPT) protocol, and (2) cross-referencing observed land-use and land-cover changes with existing planning regulations. The results of the surveys on urban development show that, between 2005 and 2011, the city showed spatial expansion, whereas between 2011 and 2017, densification mainly occurred within the existing urban extent. Between 2005 and 2017, the fraction of open LCZs increased, with the largest increase taking place between 2011 and 2017. The largest decrease was seen for low the plants (LCZ D) and agricultural greenhouse (LCZ H) categories. As the potential of LCZs as, for example, a heat stress assessment tool has been shown elsewhere, understanding the relation between policy strategies and LCZ changes is important to take rational urban planning strategies toward sustainable city development.
Calculating Set-Volume for the Limb Muscles with the Performance of Multi-Joint Exercises: Implications for Resistance Training Prescription
Authors: Schoenfeld Brad , Grgic Jozo , Haun Cody , Itagaki Takahiro , Helms Eric
Published: July 2019

Resistance training volume, determined by the number of sets performed (set-volume) is considered one of the key variables in promoting muscle hypertrophy. To better guide resistance exercise prescription for weekly per-muscle training volume, the purpose of this paper is to provide evidence-based considerations for set-volume ratios between multi-joint (MJ) and single-joint (SJ) exercises so that practitioners can better manage prescription of training volume in program design. We analyzed this topic from three primary areas of focus: (1) biomechanical and physiological factors; (2) acute research; and (3) longitudinal research. From a biomechanical and physiological standpoint, when considering force production of different muscle groups, the moment arm of a given muscle, “motor abundance”, the link between biomechanics and exercise-induced fatigue, as well as the amount of time in voluntary muscle activation, a logical rationale can be made for SJ exercises producing greater hypertrophy of the limb muscles than MJ exercises (at least from specific exercises and under certain conditions). This would mean that sets for a MJ exercise should be counted fractionally for select muscles compared to an SJ exercise (i.e., less than a 1:1 ratio) when prescribing set-volumes for given muscles. When considering results from acute studies that measured muscle activation during the performance of SJ and MJ exercises, it seems that MJ exercises are not sufficient to maximize muscle activation of specific muscles. For example, during performance of the leg press and squat, muscle activation of the hamstrings is markedly lower than that of the quadriceps. These results suggest that a 1:1 ratio cannot be assumed. Current longitudinal research comparing the effects of training with MJ vs. SJ or MJ + SJ exercises is limited to the elbow flexors and the evidence is somewhat conflicting. Until more research is conducted to derive stronger conclusions on the topic, we propose the best advice would be to view set-volume prescription on a 1:1 basis, and then use logical rationale and personal expertise to make determinations on program design. Future research should focus on investigating longitudinal hypertrophic changes between MJ and SJ in a variety of populations, particularly resistance-trained individuals, while using site-specific measures of muscle growth to more systematically and precisely compute effective individualized set-volumes.
Diagnostic Convergent Interviewing to Inform Redesign Toward Sustainable Work Systems for Paramedics
Authors: Thynne Lara , Rodwell John
Published: July 2019

Many paramedics are working under levels of fatigue that would warrant immediate removal from the workplaces in other industries and such high levels of fatigue indicate a work system that is not sustainable. Sustainable work systems (SWS) build on a sociotechnical systems approach to work redesign. To diagnose the key issues in a work system, and inform any redesign or interventions, a powerful diagnostic tool, such as convergent interviewing, may be helpful. Convergent interviewing was applied to a paramedic context, extending the standard sociotechnical systems approach to work and non-work systems. The inductive convergent interviewing process was able to encapsulate the complexity of the key issues associated with fatigue and recovery in the system that is the paramedics’ lives. The issues raised could then be used to inform system changes in a move toward more sustainable work practices for paramedics.
Science Mapping the Knowledge Base on Sustainable Human Resource Management, 1982–2019
Authors: Kainzbauer Astrid , Rungruang Parisa
Published: July 2019

The increasing interest in sustainability has led to the emergence of a new research focus in the field of human resource management (HRM). HRM scholars have recently begun to explore how HRM might contribute to sustainable outcomes and coined the term ‘sustainable human resource management’(S-HRM). In this bibliometric review, science mapping tools were used to examine 475 Scopus-indexed documents on S-HRM. The objectives of the review were to analyze the size, evolution, and regional distribution of this knowledge base, identify key journals, documents, as well as authors, examine the intellectual structure of this literature, and highlight topical trends. The review revealed a knowledge base that is still in the emergent phase, with a global scope but a concentration in Western developed societies. Four Schools of Thought emerged within this field. This review hopes to guide a new generation of S-HRM scholars by providing an overview of the current status of the knowledge base.
Multiple Cropping System Expansion: Increasing Agricultural Greenhouse Gas Emissions in the North China Plain and Neighboring Regions
Authors: Zhang Xueyan
Published: July 2019

The increase of agricultural greenhouse gas (GHG) emissions has become a significant issue for China, affecting the achievement of its Nationally Determined Contributions under the Paris Agreement. Expansion of the large-scale multiple cropping system as a consequence of climate warming could be a major driving force of this increase. In this study, life cycle assessment was employed to identify agricultural GHG emissions due to the expansion of the multiple cropping system in the North China Plain and neighboring regions. We found that agricultural greenhouse gas emissions have increased from 41.34 to 120.87 Tg CO2-eq/yr over the past 30 years, and the expansion of the multiple cropping system has contributed to 13.89% of this increment. Furthermore, the increases in straw handling and agricultural inputs which are related to multiple cropping systems have also played an important role. Results of our study demonstrate that the expansion of the multiple cropping system contributes considerably to increases in agricultural GHG emissions in the North China Plain and neighboring regions. Therefore, it can be concluded that the sustained northward expansion of the multiple cropping system will further elevate agricultural GHG emissions in China, and this should be considered while formulating policies to reduce GHG emissions from agriculture.
Structuring a Residential Satisfaction Model for Predictive Personalization in Mass Social Housing
Authors: Bunster Victor , Bustamante Waldo
Published: July 2019

Ensuring access to quality social housing is a major challenge for developing countries. The problems of standardized mass housing are well-known. However, this type of provision is ubiquitously used for its advantages when addressing pressing shortages, often resulting in significant mismatches between the attributes of the housing and the requirements of the dwellers. This multidisciplinary study explores linkages between personalized development and residential satisfaction towards informing a mass personalization approach to social housing. In specific, it presents a model that formalizes this relationship using expectancy disconfirmation theory and field information. A housing survey was conducted in four estates located in Concepción, southern Chile, and complemented with environmental performance data generated with simulation software. The analysis of the results suggests that the relationship between occupants and providers (i.e., personalization as a service) can influence the build-up of expectations, while the capacity of the dwellings to meet the requirements of different households (i.e., personalization as a product) can have a significant impact on satisfaction. These outcomes are formalized with a model that acknowledges these links at different stages of occupancy and, therefore, can be used to inform the personalized development of mass social housing.
Indoor Thermal Comfort Improvement through the Integrated BIM-Parametric Workflow-Based Sustainable Renovation of an Exemplary Apartment in Seoul, Korea
Authors: Amoruso Fabrizio M. , Dietrich Udo , Schuetze Thorsten
Published: July 2019

Apartment buildings are the most common housing typology in South Korea. The mass construction of apartment neighborhoods during a period of rapid economic growth (1970–1997) involved the minimization of material use and quality, as well as industrialized construction processes. Accordingly, apartment buildings require essential renovation after only 20 years of operation. This study focuses on the improvement of thermal comfort for the renovation of an exemplary apartment building based on an integrated Building Information Modeling (BIM) and parametric software framework. The existing apartment was reconstructed with BIM software, and the virtual model was utilized for a parametric building energy simulation to calculate the thermal comfort condition of occupants during the entire year. The thermal comfort analysis results defined the criteria for the development of an enhanced building envelope system characterized by modular panels. The parametric energy simulation was executed for the renovated apartment condition with the enhanced envelope system, and the thermal comfort improvements were quantified by comparing the results for the apartment condition before and after renovation. This study aims to provide the tools and criteria for the comfort analysis of apartment occupants, as well as propose sustainable solutions for the improvement of thermal comfort in aged buildings with similar conditions, internal distribution, and construction components.
The Role of Culture in the Self-Organisation of Coastal Fishers Sustaining Coastal Landscapes: A Case Study in Estonia
Authors: Printsmann Anu , Pikner Tarmo
Published: July 2019

The cultural sustainability of coastal landscapes relies heavily on the community’s self-organisation in fish foodways. The theoretical framework concentrates on cultural sustainability, foodways, land–sea interactions, and community of practice. The data presented in this article were part of the SustainBaltic Integrated Coastal Zone Management plan, consisting mainly of semi-structured and focus group interviews with stakeholders, supported by background information from various available sources. The results are outlined by descriptions of self-organisation, community matters, and food forming cultural sustainability of coastal landscapes. The self-organisation in community of practice among coastal fishers is slowly progressing by negotiating common resources and voicing concerns about ecological, economic, and social sustainability. Foodways, which comprise the indispensable ingredient for sustaining a way of life that has produced traditional coastal landscapes, are always evolving.
The Effect of Conservation Agriculture and Environmental Factors on CO2 Emissions in a Rainfed Crop Rotation
Authors: Carbonell-Bojollo Rosa , Veroz-Gonzalez Oscar , Ordoñez-Fernandez Rafaela , Moreno-Garcia Manuel , Basch Gottlieb , Kassam Amir , Repullo-Ruiberriz de Torres Miguel A. , Gonzalez-Sanchez Emilio J.
Published: July 2019

There are many factors involved in the release of CO2 emissions from the soil, such as the type of soil management, the soil organic matter, the soil temperature and moisture conditions, crop phenological stage, weather conditions, residue management, among others. This study aimed to analyse the influence of these factors and their interactions to determine the emissions by evaluating the environmental cost expressed as the kg of CO2 emitted per kg of production in each of the crops and seasons studied. For this purpose, a field trial was conducted on a farm in Seville (Spain). The study compared Conservation Agriculture, including its three principles (no-tillage, permanent soil cover, and crop rotations), with conventional tillage. Carbon dioxide emissions measured across the four seasons of the experiment showed an increase strongly influenced by rainfall during the vegetative period, in both soil management systems. The results of this study confirm that extreme events of precipitation away from the normal means, result in episodes of high CO2 emissions into the atmosphere. This is very important because one of the consequences for future scenarios of climate change is precisely the increase of extreme episodes of precipitation and periods extremely dry, depending on the area considered. The total of emission values of the different plots of the study show how the soils under the conventional system (tillage) have been emitting 67% more than soils under the conventional agriculture system during the 2010/11 campaign and 25% for the last campaign where the most appreciable differences are observed.
City Brand: What Are the Main Conditions for Territorial Performance?
Authors: Ferreira Paulo , Dionísio Andreia
Published: July 2019

Territories and respective political agents recognize now the importance of being attractive, not only because of tourism, but also because this is an important feature to attract investment and even new residents. Based on this evolution, the concept of territory branding has been developed, with rankings like the Portugal City Brand measuring it. With the objective of explaining the most important conditions for territories to attain higher city branding and based on a large dataset, a factor analysis was applied to identify possible components to be used. With those components and using a fuzzy-set qualitative comparative analysis, the main conditions for a better position in the ranking are identified. Results point to better identification of conditions to distinguish lower positioned municipalities, namely lack of economic conditions, of general conditions and low demographic indicators. Moreover, it is possible to conclude that the conditions of the different sub-rankings are different from the ones of the main ranking.
Assessment of the Potential Use of Young Barley Shoots and Leaves for the Production of Green Juices
Authors: Blicharz-Kania Agata , Andrejko Dariusz , Kluza Franciszek , Rydzak Leszek , Kobus Zbigniew
Published: July 2019

It is possible to use the aboveground parts of barley, which are cultivated as a forecrop. They are often simply composted or dried for bedding. It is worth trying other more effective methods of processing aboveground biomass. The aim of this study was to preliminary investigate the possibility of using young barley leaves and shoots for the production of green juice with potential health properties. The material was collected at days 7, 14, 21, and 28 after plant emergence. The length and strength of the shoots were measured and the pressing yield was calculated. The pH value and the content of protein, chlorides, and reducing sugars were also determined. The juice was additionally subjected to pasteurisation and freezing, and changes in pH and chlorophyll content occurring during storage were determined. The pressing yield of young barley leaves and shoots was estimated to be between 69% and 73%. The product was characterised by a high content of total protein (34.45%–51.81%d.w.) and chlorophylls (6.62 mg·g−1). The chlorophyll content declined during barley juice storage. Pasteurisation of the juice from young barley leaves does not induce statistically significant changes in the pH of the juice, but reduces the chlorophyll content. Our results revealed that the most effective way to preserve the green juice is by freezing. This process does not induce changes in juice acidity and only slightly reduces the chlorophyll content during storage of the product.
Perceptions of Priority Policy Areas and Interventions for Urban Sustainability in Polish Municipalities: Can Polish Cities Become Smart, Inclusive and Green?
Authors: Przywojska Justyna , Podgórniak-Krzykacz Aldona , Wiktorowicz Justyna
Published: July 2019

The transition to sustainable urban development requires both appropriate city management and local authorities that are aware of the implications posed by new urban sustainability challenges. The article aims to identify the priority policy/practice areas and interventions to solve sustainability challenges in Polish municipalities, as well as the factors that differentiate these priorities. Through an online questionnaire we surveyed 460 Polish municipalities, and conducted a multidimensional assessment concerning how mayors (and their executive teams) prioritise possible policy/practice areas and interventions related to sustainability. Our analysis implies that the mayors (and their executive teams) assign higher priority to policy/practice areas and interventions related to economic and social domains, and slightly lower priority to environmental ones. However, an important finding is that the priority policy/practice areas and interventions do not correspond well to some of the contemporary sustainability challenges in Polish cities. Effectively tackling urban environmental, economic and social problems would require the implementation of new approaches related to smart cities, the circular economy and/or cultural diversity. However, these less traditional policy/practice areas and interventions are quite low on the priority list of Polish mayors and their executive teams. Interestingly mayors and executive teams that prefer more participatory and solidarity-based management approaches are more likely to prioritise less traditional policy/practice areas and interventions to solve urban sustainability challenges in their municipalities.
Exploring the Proactivity Levels and Drivers of Environmental Strategies Adopted by Vietnamese Seafood Export Processing Firms: A Qualitative Approach
Authors: Do Binh , Nguyen Uyen , Nguyen Ninh , Johnson Lester W.
Published: July 2019

Export processing firms from emerging markets often need to adjust their export strategies towards environmentally friendly directions to address strict regulatory requirements and increasingly environmental concerns among the public and consumers in advanced countries. This study aims to explore and evaluate different proactivity levels and drivers of environmental strategies (ESs) adopted by Vietnamese seafood export processing firms. Data was obtained from two sources: Public archival data of 32 listed firms, and semi-structured interviews with 44 managers from seafood export processing firms. Content analysis revealed that reactive ESs were adopted the most by Vietnamese seafood export processing firms, followed by opportunistic ESs, focused ESs and proactive ES, respectively. The findings also demonstrated that both internal factors and external factors in home and host countries motivate the firms to pursue different ESs. This study sheds light on unexplored characteristics and drivers of ESs in Vietnam and it assists key stakeholders including export processing firms and policymakers in the adoption, development and promotion of ESs.
Association Rule Mining Tourist-Attractive Destinations for the Sustainable Development of a Large Tourism Area in Hokkaido Using Wi-Fi Tracking Data
Authors: Arreeras Tosporn , Arimura Mikiharu , Asada Takumi , Arreeras Saharat
Published: July 2019

The rise of radiofrequency scanner technology has led to its potential application in the observation of people’s movements. This study used a Wi-Fi scanner device to track tourists’ traveling behavior in Hokkaido’s tourism area, which occupies a large region that features a unique natural landscape. Inbound tourists have significantly increased in recent years; thus, tourism’s sustainability is considered to be important for maintaining the tourism atmosphere in the long term. Using internet-enabled technology to conduct extensive area surveys can overcome the limitations imposed by conventional methods. This study aims to use digital footprint data to describe and understand traveler mobility in a large tourism area in Hokkaido. Association rule mining (ARM)—a machine learning methodology—was performed on a large dataset of transactions to identify the rules that link destinations visited by tourists. This process resulted in the discovery of traveling patterns that revealed the association rules between destinations, and the attractiveness of the destinations was scored on the basis of visiting frequency, with both inbound and outbound movements considered. A visualization method was used to illustrate the relationships between destinations and simplify the mathematical descriptions of traveler mobility in an attractive tourism area. Hence, mining the attractiveness of destinations in a large tourism area using an ARM method integrated with a Wi-Fi mobility tracking approach can provide accurate information that forms a basis for developing sustainable destination management and tourism policies.
A Study on the Limitations of South Korea’s National Roadmap for Greenhouse Gas Reduction by 2030 and Suggestions for Improvement
Authors: Ha Sungkyun , Tae Sungho , Kim Rakhyun
Published: July 2019

South Korea must submit its targets for greenhouse gas reduction by 2030 to comply with the Paris Agreement. While South Korea’s government has announced a roadmap for achieving greenhouse gas reduction targets by 2030, issues are present regarding the methodology used to set reduction targets, select the reduction method, and estimate the potential emissions reduction in the building sector. Accordingly, the present study identified the limitations based on an analysis of the roadmap and suggested an improvement plan for each limitation. To improve the roadmap, the methodology used to set emissions targets was changed from business-as-usual (BAU) to the absolute emissions method, the Intergovernmental Panel on Climate Change (IPCC) guidelines were applied to estimate greenhouse gas emissions, and methodology for determining emissions targets by year was proposed. The reduction method has been proposed abstractly, and five methods have been suggested: Energy consumption by building age and establishment of gross floor area for cooling/heating, supply status for each type of lighting, estimation of reduction amount through supply of LED lighting, reduction amount estimation by analyzing current supply status data for home appliances and office equipment, proposal of methodology for improvement of duplicate estimation for building energy maintenance systems (BEMS), and estimation of reduction potential by applying efficiency improvement in power generating equipment.
Some Novel Picture 2-Tuple Linguistic Maclaurin Symmetric Mean Operators and Their Application to Multiple Attribute Decision Making
Authors: Feng Min , Geng Yushui
Published: July 2019

When solving multiple attribute decision making (MADM) problems, the 2-tuple linguistic variable is an effective tool that can not only express complex cognitive information but also prevent loss of information in calculation. The picture fuzzy set (PFS) has three degrees and has more freedom to express cognitive information. In addition, Archimedean t-conorm and t-norm (ATT) can generalize most existing t-conorms and t-norms and Maclaurin symmetric mean (MSM) operators can catch the relationships among the multi-input parameters. Therefore, we investigate several novel aggregation operators, such as the picture 2-tuple linguistic MSM (2TLMSM) operator based on the ATT (ATT-P2TLMSM) and the picture 2-tuple linguistic generalized MSM (2TLGMSM) operator based on ATT (ATT-P2TLGMSM). Considering that the input parameters have different importance, we proposed picture 2-tuple linguistic weighted MSM (2TLWMSM) operators based on ATT (ATT-P2TLWMSM) and picture 2-tuple linguistic weighted generalized MSM (2TLWGMSM) operators based on ATT (ATT-P2TLWGMSM). Finally, a MADM method is introduced, and an expositive example is presented to explain the availability and applicability of the developed operators and methods.