bluuebunny/crossref_metadata_2025 huggingface dataset:
A 0.6-µW Chopper Amplifier Using a Noise-Efficient DC Servo Loop and Squeezed-Inverter Stage for Power-Efficient Biopotential Sensing
Authors: Pham Xuan Thanh , Nguyen Ngoc Tan , Nguyen Van Truong , Lee Jong-Wook
Published: April 2020

To realize an ultra-low-power and low-noise instrumentation amplifier (IA) for neural and biopotential signal sensing, we investigate two design techniques. The first technique uses a noise-efficient DC servo loop (DSL), which has been shown to be a high noise contributor. The proposed approach offers several advantages: (i) both the electrode offset and the input offset are rejected, (ii) a large capacitor is not needed in the DSL, (iii) by removing the charge dividing effect, the input-referred noise (IRN) is reduced, (iv) the noise from the DSL is further reduced by the gain of the first stage and by the transconductance ratio, and (v) the proposed DSL allows interfacing with a squeezed-inverter (SQI) stage. The proposed technique reduces the noise from the DSL to 12.5% of the overall noise. The second technique is to optimize noise performance using an SQI stage. Because the SQI stage is biased at a saturation limit of 2VDSAT, the bias current can be increased to reduce noise while maintaining low power consumption. The challenge of handling the mismatch in the SQI stage is addressed using a shared common-mode feedback (CMFB) loop, which achieves a common-mode rejection ratio (CMRR) of 105 dB. Using the proposed technique, a capacitively-coupled chopper instrumentation amplifier (CCIA) was fabricated using a 0.18-µm CMOS process. The measured result of the CCIA shows a relatively low noise density of 88 nV/rtHz and an integrated noise of 1.5 µVrms. These results correspond to a favorable noise efficiency factor (NEF) of 5.9 and a power efficiency factor (PEF) of 11.4.
Industrial Clusters as Drivers of Sustainable Regional Economic Development? An Analysis of an Automotive Cluster from the Perspective of Firms’ Role
Authors: Chen Xiaofei , Wang Enru , Miao Changhong , Ji Lili , Pan Shaoqi
Published: April 2020

This paper examined the relationships among firms in a rapidly growing specialized industrial cluster—the Chery automotive cluster located in the Wuhu Economic and Technology Development in eastern China. After demonstrating how the Chery automotive cluster contributed to sustainable regional economic development, it focused on defining the roles that major firms play in the localized production network. Based on three attributes of the firm (network linkages, network position, and network power), the study identified a typology of firms’ role, including the dominant core, lead firms, gatekeepers, intermediaries, club of foreigners, peripherals, and loners. By revealing the heterogeneity of the firms and discussing the differing roles they play in the network, the paper made some policy recommendations to promote the sustainable development of the cluster, including providing policy supports to core firms, encouraging inter-firm networking and interaction, and diversifying the cohort of gatekeepers.
Measuring Energy Performance for Regional Sustainable Development in China: A New Framework based on a Dynamic Two-Stage SBM Approach
Authors: Chiu Sheng-Hsiung , Lin Tzu-Yu , Yang Hai-Lan
Published: April 2020

Sustainable development has always been an important issue for all policy makers, even more so now, as global warming has seriously threatened the whole world. To understand the efficacy of regional sustainable policies, we proposed a dynamic, two-stage, slacks-based measure (SBM) model with carry-over and intermediate variables, highlighting the importance of an electricity portfolio, to measure overall energy performance for the purpose of regional sustainable development. In this unified linear programming framework with intertemporal evaluation, we estimated the effects of a clean electricity supply by the abatement of CO2 emissions and the gain of economic growth. The results can be used as a reference for decision makers to shape regional sustainable development policies. Using data of 30 provincial administration regions in China for the period of 2012–2017, we postulate that the lower energy performance of the Chinese regional economic system for sustainable development may be attributed to a lower electricity portfolio performance. We then postulate that investment in low-carbon energy infrastructure can combat CO2 emissions, and is also a major driving force in the regional economic growth.
Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
Authors: van Leeuwen Boudewijn , Tobak Zalán , Kovács Ferenc
Published: April 2020

Changing climate is expected to cause more extreme weather patterns in many parts of the world. In the Carpathian Basin, it is expected that the frequency of intensive precipitation will increase causing inland excess water (IEW) in parts of the plains more frequently, while currently the phenomenon already causes great damage. This research presents and validates a new methodology to determine the extent of these floods using a combination of passive and active remote sensing data. The method can be used to monitor IEW over large areas in a fully automated way based on freely available Sentinel-1 and Sentinel-2 remote sensing imagery. The method is validated for two IEW periods in 2016 and 2018 using high-resolution optical satellite data and aerial photographs. Compared to earlier remote sensing data-based methods, our method can be applied under unfavorite weather conditions, does not need human interaction and gives accurate results for inundations larger than 1000 m2. The overall accuracy of the classification exceeds 99%; however, smaller IEW patches are underestimated due to the spatial resolution of the input data. Knowledge on the location and duration of the inundations helps to take operational measures against the water but is also required to determine the possibilities for storage of water for dry periods. The frequent monitoring of the floods supports sustainable water management in the area better than the methods currently employed.
The Sustainable Positive Effects of Enterprise Social Media on Employees: The Visibility and Vicarious Learning Lens
Authors: Sun Yuan , Ding Zhebin , Zhang Zuopeng (Justin) , Gauthier Jeffrey
Published: April 2020

The proliferation of enterprise social media (ESM) has resulted in a research domain focused on its potential influence on the sustainable development of enterprises. Visibility has been increasingly applied as a useful lens through which to explore the effects of ESM. However, most prior research either has not addressed the multi-dimensionality of this concept or has not fully explored its dimensions separately. To bridge this knowledge gap, this paper identifies four categories of visibility to explore how they affect the process of an individual’s vicarious learning. We propose eight theoretical propositions and verify them through a confirmatory case study. The results show that each type of visibility affects the vicarious learning process in its own unique manner. Our research makes significant contributions to the literature by extending the existing implications of vicarious learning and ESM visibility and investigating their relationships, laying a strong foundation for further theoretical work. In addition, our research provides valuable insights and guidance for ESM practitioners.
Innovative Resources, Promotion Focus and Responsible Innovation: The Moderating Roles of Adaptive Governance
Authors: Cao Xia , Lv Dan , Xing Zeyu
Published: April 2020

This paper discusses the relationship between innovative resources, promotion focus, adaptive governance and responsible innovation. In accordance with the path of “demand—motivation—behavior”, this paper takes adaptive governance as the moderator, and constructs an influence relationship model of “innovative resources—promotion focus (adaptive governance)—responsible innovation”. Then this paper takes 361 managers from above the middle management level and the technical personnel of enterprises as the investigation objects, and conducts empirical research by using the structural equation model. The results show that: (1) innovative resources have a significant positive impact on responsible innovation; (2) promotion focus partially mediates the effect of innovative resources on responsible innovation; (3) adaptive governance has a positive moderating effect on the relationship between innovative resources and responsible innovation. The results enrich the quantitative research of responsible innovation, reveal the internal mechanism of innovative resources affecting responsible innovation, provide a new way for technological innovation governance and provide a new way of thinking for the transformation from the traditional innovation paradigm into a sustainable innovation paradigm.
Big Data Manifestation in Municipal Waste Management and Cryptocurrency Sectors: Positive and Negative Implementation Factors
Authors: Limba Tadas , Novikovas Andrejus , Stankevičius Andrius , Andrulevičius Antanas , Tvaronavičienė Manuela
Published: April 2020

Two mainstream topics have been widely discussed over the past few years: ways to reduce the human impact on nature and the way that the industrial revolution 4.0 changes industries. The aim of this research topic is to analyse the positive and negative factors of big data implementation in the sector of cryptocurrency (as part of the industrial revolution 4.0) and in the sector of municipal waste management. The analysis reveals the differences and similarities between the cryptocurrency and municipal waste management sectors in the context of big data. The findings are significant for the estimation of the technological development of digitalized and non-digitalized sectors.
Conceptual Planning of Urban–Rural Green Space from a Multidimensional Perspective: A Case Study of Zhengzhou, China
Authors: Mu Bo , Liu Chang , Tian Guohang , Xu Yaqiong , Zhang Yali , Mayer Audrey L. , Lv Rui , He Ruizhen , Kim Gunwoo
Published: April 2020

The structure and function of green-space system is an eternal subject of landscape architecture, especially due to limited land and a need for the coordinated development of PLEs (production, living, and ecological spaces). To make planning more scientific, this paper explored green-space structure planning via multidimensional perspectives and methods using a case study of Zhengzhou. The paper applies theories (from landscape architecture and landscape ecology) and technologies (like remote sensing, GIS—geographic information system, graph theory, and aerography) from different disciplines to analyze current green-space structure and relevant physical factors to identify and exemplify different green-space planning strategies. Overall, our analysis reveals that multiple green-space structures should be considered together and that planners and designers should have multidisciplinary knowledge. For specific strategies, the analysis finds (i) that green complexes enhance various public spaces and guide comprehensive development of urban spaces; (ii) that green ecological corridors play a critical role in regional ecological stability through maintaining good connectivity and high node degree (Dg) and betweenness centrality index (BC) green spaces; (iii) that greenway networks can integrate all landscape resources to provide more secured spaces for animals and beautiful public spaces for humans; (iv) that blue-green ecological networks can help rainwater and urban flooding disaster management; and (v) that green ventilation corridors provide air cleaning and urban cooling benefits, which can help ensure healthy and comfortable urban–rural environments. In our view, this integrated framework for planning and design green-space structure helps make the process scientific and relevant for guiding future regional green-space structure.
Hematite/Graphitic Carbon Nitride Nanofilm for Fenton and Photocatalytic Oxidation of Methylene Blue
Authors: Lee Sangbin , Park Jae-Woo
Published: April 2020

Hematite (α-Fe2O3)/graphitic carbon nitride (g-C3N4) nanofilm catalysts were synthesized on fluorine-doped tin oxide glass by hydrothermal and chemical vapor deposition. Scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy analyses of the synthesized catalyst showed that the nanoparticles of g-C3N4 were successfully deposited on α-Fe2O3 nanofilm. The methylene blue degradation efficiency of the α-Fe2O3/g-C3N4 composite catalyst was 2.6 times greater than that of the α-Fe2O3 single catalyst under ultraviolet (UV) irradiation. The methylene blue degradation rate by the α-Fe2O3/g-C3N4 catalyst increased by 6.5 times after 1 mM of hydrogen peroxide (H2O2) was added. The photo-Fenton reaction of the catalyst, UV, and H2O2 greatly increased the methylene blue degradation. The results from the scavenger experiment indicated that the main reactants in the methylene blue decomposition reaction are superoxide radicals photocatalytically generated by g-C3N4 and hydroxyl radicals generated by the photo-Fenton reaction. The α-Fe2O3/g-C3N4 nanofilm showed excellent reaction rate constants at pH 3 (Ka = 6.13 × 10−2 min−1), and still better efficiency at pH 7 (Ka = 3.67 × 10−2 min−1), compared to other methylene blue degradation catalysts. As an immobilized photo-Fenton catalyst without iron sludge formation, nanostructured α-Fe2O3/g-C3N4 are advantageous for process design compared to particle-type catalysts.
Women Participation: A Productivity Strategy in Rice Production
Authors: Rasheed Abubakar , Mwalupaso Gershom Endelani , Abbas Qasir , Tian Xu , Waseem Rafay
Published: April 2020

Agriculture is an important engine for economic growth and a vigorous driver of poverty reduction in developing countries. In Pakistan, rice production is one of the most essential sectors. However, it has been underperforming, largely because of low women’s participation, which is often a crucial resource in agriculture and the rural economy. Unfortunately, previous studies have seldom recognized and emphasized the role of women in triggering agricultural and rural development. We address this research gap using 300 farm households’ survey data forms collected from Pakistan farmers by applying the stochastic frontier analysis. The results indicate that women’s participation is associated with higher labor/land ratio, land productivity, and finally improved technical efficiency. Precisely, women’s participation increased technical efficiency (TE) by 47.3%. Interestingly, in view of previous studies, this evidence is not sporadic. Overall, our study provides some evidence to promote women’s participation in rice production, as such empowerment of women holds great potential to enhance agricultural production, which is consistent with the aim of sustainable development goals (SDGs).
Does Foreign Direct Investment Affect Tropospheric SO2 Emissions? A Spatial Analysis in Eastern China from 2011 to 2017
Authors: Yan Yuxiang , Hu Wusheng
Published: April 2020

Air pollution has attracted much attention worldwide. Sulfur dioxide (SO 2 ) is a major air pollutant in cities and affects human health seriously. The purpose of this paper is to examine how foreign direct investment affects SO 2 emissions and whether the pollution haven hypothesis exists in eastern China. On basis of the detailed data, we performed the spatial autocorrelation analysis and the spatial regression analysis. The results show that an increase in the foreign direct investment in a city is associated with a decline in SO 2 emissions in the same city, indicating that the pollution haven hypothesis does not hold in eastern China. But the spillover effect of the foreign direct investment is positive, indicating that a larger foreign direct investment in neighboring cities tends to raise SO 2 emissions in the local city.
Using Simulation to Develop Divergent and Reflective Thinking in Teacher Education
Authors: Zach Sima , Ophir Miki
Published: April 2020

Purpose: This study examined the influence of simulation on flexible and reflective thinking in student teachers (STs), and appraised how they evaluate its potential contribution to teacher education programs. Method: Twenty-three Israeli physical education STs participated in a simulation course. They planned teaching-learning conflict scenarios, and served as actors or volunteers in these scenarios, which were filmed and discussed. Discussions were videotaped and transcribed. Content analyses were conducted on the discussions and the written reflections. Results: STs not only increased their flexible and reflective thinking, but they gained an understanding of how to do it independently. As they were learning how to be more open-minded, they were able to feel, think, and behave authentically, and to offer a variety of solutions regarding conflictual situations. Conclusion: STs developed flexible and reflective thinking, and widened their repertoire of behaviors that succeeded in integrating thoughts and feelings into learning-teaching situations.
Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System
Authors: Zhou Lixin , Lin Jie , Li Yanfeng , Zhang Zhenyu
Published: April 2020

Mobile application innovation diffusion can be used to enhance the reputation and competitiveness of Internet enterprises. However, few works have explored the process of mobile application innovation diffusion from the individual perspective. Therefore, this paper employs multi-agent methods to simulate the innovation diffusion of mobile applications from the perspective of social networks. Specifically, we combine psychology, sociology, game theory and network effect theory to model user behaviors of adoption and rejection decisions for mobile applications. The multi-agent model was built in Anylogic 8 to simulate the communication and interaction between individual users. Then, this paper discusses the evolution of decision-making of social network user groups with different network structures and network effects. We also investigate the impact of different firms’ promotion on innovation diffusion. Our findings suggest firms could make better strategies and achieve better diffusion effects from mobile applications.
An AHP-SWOT-Fuzzy TOPSIS Approach for Achieving a Cross-Border RES Cooperation
Authors: Papapostolou Aikaterini , Karakosta Charikleia , Apostolidis Georgios , Doukas Haris
Published: April 2020

The emerging need to tackle climate change and mitigate greenhouse gas emissions has led to the consolidation of interest in renewable energy sources (RES) setting specific targets in the European area. To achieve the ambitious targets set, Member States are given the opportunity to cooperate with one or more of their developing neighboring countries. The aim of this paper is to develop a methodological framework based on the combination of the Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis with the Analytic Hierarchy Process (AHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) methods for adopting the most appropriate strategic plan, in order to establish a successful energy cooperation that will create beneficial conditions for all the involved parties. The results could be important in facilitating decision makers to assess the role and design of this cooperation mechanism. Key insights will also emerge with regards to opportunities for energy strategy cooperation between Europe and its neighboring countries.
Historical Cloisters and Courtyards as Quiet Areas
Authors: Masullo Massimiliano , Castanò Francesca , Toma Roxana Adina , Maffei Luigi
Published: April 2020

Searching for renovating and/or constructing quiet areas in historical urban sites, along with the conservation and valorization policies of the tangible and intangible value of historic urban sites are goals that can be combined into a unique sustainable strategy for the preservation of the sense of place and identity of communities as well as their well-being. Historic cloisters and courtyards are examples of such sites. Due to their physical, architectural, environmental and cultural features, they present restorative capabilities that could qualify them as quite areas. This paper aims to establish a new procedure that, through the exploration and analysis of past and current aspects of these sites, makes it possible to classify them and understand whether they still preserve a restorative character. A graphic representation, obtained from a historical analysis and an objective description of past and current historical/architectural, environmental and cultural scenarios, has been used. The results were compared with those of the Perceived Restorativeness Scale (PRS-11). A diamond shape represents highly restorative sites, while deviations from this shape were found to be weakly correlated with a restorative nature. This has also been shown by the high positive correlation of analytical parameters with the PRS-11 score and, in particular, with the component of Fascination.
Housing Choices of Older People: Staying or Moving in the Case of High Care Needs
Authors: Filipovič Hrast Maša , Sendi Richard , Kerbler Boštjan
Published: April 2020

Despite the development of various housing options across Europe, older people often face the choice of staying at home with the support of family and/or formal services or moving to a care home, but how people vary regarding these preferences and how newer cohorts will be different is under-researched. This study explores the housing choices of older people under the condition of liminality, which is defined as the hypothetical condition of high care needs. The most common choices available are compared; that is, staying at home (with social home-care support or visits to a daycare centre) or moving to supported housing or a care home. Cluster analysis revealed five distinct groups of older people that were differentiated in their choices between various options of moving versus staying at home, either by using home care or daycare. Differences between the clusters along three dimensions that influence decisions to move or stay, namely levels of attachment, satisfaction with housing and availability of support, which often function as limits on the options that are preferred, were explored. The results present the complexity of the decision-making process under imagined conditions of liminality and show a great diversity among people’s preferences. They also indicate that a significant share of older people have a strong preference for only one option (two of the cluster groups).
Determining Factors in MOOCs Completion Rates: Application Test in Energy Sustainability Courses
Authors: Romero-Rodríguez Luis M. , Ramírez-Montoya María Soledad , Aguaded Ignacio
Published: April 2020

Massive Online Open Courses (MOOCs) are open educational activities that allow for distance learning and professional updating, although the academic community has questioned their effectiveness due to their low completion rates. This research analyzes which factors (personal, family, social, labor, and instructional design) are involved in the value expectations and engagement of the MOOCs and to what degree these affect the decision to enroll and the completion of the MOOC. To this end, in the context of 12 MOOCs on energy sustainability carried out between 2017 and 2018, 8737 participants were surveyed using two instruments designed according to theoretical constructs and expert judgment. The main results show that all the factors reviewed influence the decision to take a MOOC, although the “professional development” aspect has the most significant impact on participants who have graduated from technical and engineering careers. Additionally, this study emphasizes that the “instructional design” factor is decisive in the engagement of younger participants, showing that the conventional design of xMOOCs (Stanford Model) may be one of the most important reasons for the low completion rates of this type of course.
Removing Sr(II) and Cs(I) from the Aqueous Phase Using Basil Seed and Elucidating the Adsorption Mechanism
Authors: Uematsu Yugo , Ogata Fumihiko , Saenjum Chalermpong , Nakamura Takehiro , Kawasaki Naohito
Published: April 2020

To confirm the capability and mechanisms of Sr(II) and Cs(I) adsorption from the aqueous phase using basil seed (BS), virgin BS, calcined BS (BS500 and BS1000), and enzymatically treated BS, namely Mannanase BGM (M-BS), Pectinase G (P-BS), Hemicellulase (H-BS), and Cellulase A (C-BS) was evaluated. The adsorption capabilities of Sr(II) and Cs(I) of various BS adsorbents were also evaluated. The quantity of Sr(II) and Cs(I) adsorbed onto BS was greater than that of BS500 or BS1000, suggesting that the physicochemical characteristics of the BS surface affected Sr(II) and Cs(I) removal from the aqueous phase. Furthermore, the quantity of Sr(II) and Cs(I) adsorbed onto virgin BS was greater than that of enzymatically treated BS, indicating that glucomannan or (1,4)-xylan in the cellulosic hydrocolloid of the BS strongly affected the adsorption capability of Cs(I) or Sr(II) (except for M-BS in Sr(II) adsorption). Our obtained results indicate that, as an adsorbent, BS was capable of removing Sr(II) and Cs(I) from the aqueous solution.
Comparison and Bias-Correction of Satellite-Derived Precipitation Datasets at Local Level in Northern Kenya
Authors: Vigna Ingrid , Bigi Velia , Pezzoli Alessandro , Besana Angelo
Published: April 2020

Understanding ongoing trends at local level is fundamental in research on climate change. However, in the Global South it is hampered by a lack of data. The scarcity of land-based observed data can be overcome through satellite-derived datasets, although performance varies according to the region. The purpose of this study is to compute the normal monthly values of precipitation for the eight main inhabited areas of North Horr Sub-County, in northern Kenya. The official decadal precipitation dataset from the Kenyan Meteorological Department (KMD), the Global Precipitation Climatology Centre (GPCC) monthly dataset and the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) monthly dataset are compared with the historical observed data by means of the most common statistical indices. The GPCC showed the best fit for the study area. The Quantile Mapping correction is applied to combine the high resolution of the KMD dataset with the high performance of the GPCC set. A new and more reliable bias-corrected monthly precipitation time series for 1983–2014 results for each location. This dataset allows a detailed description of the precipitation distribution through the year, which can be applied in the climate change adaptation and tailored territorial planning.
Anomaly Detection System for Water Networks in Northern Ethiopia Using Bayesian Inference
Authors: Tashman Zaid , Gorder Christoph , Parthasarathy Sonali , Nasr-Azadani Mohamad M. , Webre Rachel
Published: April 2020

For billions of people living in remote and rural communities in the developing countries, small water systems are the only source of clean drinking water. Due to the rural nature of such water systems, site visits may occur infrequently. This means broken water systems can remain in a malfunctioning state for months, forcing communities to return to drinking unsafe water. In this work, we present a novel two-level anomaly detection system aimed to detect malfunctioning remote sensored water hand-pumps, allowing for a proactive approach to pump maintenance. To detect anomalies, we need a model of normal water usage behavior first. We train a multilevel probabilistic model of normal usage using approximate variational Bayesian inference to obtain a conditional probability distribution over the hourly water usage data. We then use this conditional distribution to construct a level-1 scoring function for each hourly water observation and a level-2 scoring function for each pump. Probabilistic models and Bayesian inference collectively were chosen for their ability to capture the high temporal variability in the water usage data at the individual pump level as well as their ability to estimate interpretable model parameters. Experimental results in this work have demonstrated that the pump scoring function is able to detect malfunctioning sensors as well as a change in water usage behavior allowing for a more responsive and proactive pump system maintenance.
The Contribution of Sustainable Development Goals and Forest-Related Indicators to National Bioeconomy Progress Monitoring
Authors: Linser Stefanie , Lier Markus
Published: April 2020

A sustainable and circular bioeconomy is a pathway to the achievement of the United Nations Sustainable Development Goals (SDGs) by 2030 because the bioeconomy relates to a number of SDGs. We therefore focused on whether and how these SDGs are considered in national bioeconomy strategies, and on their indicator-based progress monitoring and assessment. This paper is based on eight countries that already have elaborated indicators in their national bioeconomy strategies. We analyzed the coverage of SDG issues in national bioeconomy strategies and the indicators used. We focused on how the different national indicators used to monitor the progress of the bioeconomy are related to the SDGs indicators and the already well established and widely applied intergovernmental regional or international forest-related indicators, as the forest sector is one of the key sectors for the development of a bioeconomy. Our material and methods are based on a document review and qualitative analysis of national bioeconomy strategies and their inherent indicator sets for progress monitoring. Based on our findings on the coverage of SDG-related issues of up to 14 out of the 17 SDGs in the bioeconomy strategies and of the high share of forest-related indicators within the bioeconomy indicators used, we derive recommendations for the further development of bioeconomy indicators. Our paper does not contribute to proposing the most suitable indicators, but it does encourage national and regional actors to carefully and holistically develop their bioeconomy monitoring systems using synergies from the already existing SDGs and forest monitoring processes.
Population Dynamics of the ‘Golden Tides’ Seaweed, Sargassum horneri, on the Southwestern Coast of Korea: The Extent and Formation of Golden Tides
Authors: Choi Sun Kyeong , Oh Hyun-Ju , Yun Suk-Hyun , Lee Hyuk Je , Lee Kyounghoon , Han Young Seok , Kim Sangil , Park Sang Rul
Published: April 2020

Since 2015, troublesome masses of floating Sargassum horneri have been introduced via ocean currents and winds to the southwestern coastline of Korea, including Jeju Island. These massive mats have caused considerable damage to the aquaculture industry, tourism, and the marine ecosystem. Most previous studies of S. horneri have focused on cultivation, the development of gene markers, and photosynthetic activity, but few data on population dynamics are available. We investigated the population dynamics of native S. horneri off the southwestern coast of Korea with the aim of predicting the formation of golden tides. Populations at two sites had obligate annual life cycles. Thalli were recruited during the period September–November, grew during the period December–April, and senesced by July. This pattern reflected seasonal trends in water temperature. Specific growth rates and heights of the thalli at Munseom were significantly higher than those at Jindo. The greatest environmental difference between the two sites is probably the degree of exposure to wave action. Mortality density (thalli lost per unit area) in the Munseom population was highest during the period December–January (i.e., 2–3 months after recruitment) and in March. Most thalli in the Jindo population died off in July when water temperatures increased. The maximum average biomass of S. horneri thalli detaching from the substrata reached 1.6 kg fresh weight m–2 during January and March. Thus, large-scale drifting mats were formed by S. horneri detachment from the substrata. Despite the differences in space and environment between China and Korea, our findings will enable quantitative assessments of the overall floating Sargassum biomass in the East China and Yellow Seas.
Realizing the Environmental Benefits of Proactive Environmental Strategy: The Roles of Green Supply Chain Integration and Relational Capability
Authors: Li Suicheng , Qiao Jianqi , Cui Hecheng , Wang Shuang
Published: April 2020

Although the impact of proactive environmental strategies on corporate performance has been extensively discussed in academia, the path of the impact of proactive environmental strategies on environmental performance remains unclear. In this study, we introduce a strategy–structure–performance (SSP) framework to explore the mechanism through which proactive environmental strategies improve environmental performance by utilizing green supply chain integration. Based on the questionnaire survey data of 252 Chinese manufacturing firms, a structural equation model was established to verify our hypothesis. The results show that firms that implement a proactive environmental strategy tend to promote the green integration of suppliers through internal green integration and thus improve their environmental performance. By distinguishing two kinds of activities of green supplier integration (greening the supplier and environmental collaboration with the supplier), we found that environmental collaboration with the supplier can directly promote the environmental performance of manufacturing enterprises, but supplier greening indirectly enhances the environmental performance of enterprises through supplier environmental collaboration. The boundary conditions of the influence of internal green integration on green supplier integration are discussed, and we found that the relationship cability plays a moderating role in the influence of internal green integration on supplier green integration.
The Stochastic Annuity Method for Supporting Maintenance Costs Planning and Durability in the Construction Sector: A Simulation on a Building Component
Authors: Fregonara Elena , Ferrando Diego Giuseppe
Published: April 2020

Service life estimate is crucial for evaluating the economic and environmental sustainability of projects, by means—adopting a life cycle perspective—of the Life Cycle Cost Analysis (LCCA). Service life, in turn, is strictly correlated to maintenance investment and planning activities, in view of building/building component/system/infrastructure products’ durability requirements, and in line with the environmental-energy policies, transposed into EU guidelines and regulations. Focusing on the use-maintenance-adaptation stage in the constructions’ life cycle, the aim of this work is to propose a methodology for supporting the “optimal maintenance planning” in function of life cycle costs, assuming the presence of financial constraints. A first research step is proposed for testing the economic sustainability of different project options, at the component scale, which imply different cost items and different maintenance-replacement interventions over time. The methodology is based on the Annuity Method, or Equivalent Annual Cost approach, as defined by the norm EN 15459-1:2017. The method, poorly explored in the literature, is proposed here as an alternative to the Global Cost approach (illustrated in the norm as well). Due to the presence of uncertainty correlated to deterioration processes and market variability, the stochastic Annuity Method is modeled by introducing flexibility in input data. Thus, with the support of Probability Analysis and the Monte Carlo Method (MCM), the stochastic LCCA, solved through the stochastic Equivalent Annual Cost, is used for the economic assessment of different maintenance scenarios. Two different components of an office building project (a timber and an aluminum frame), are assumed as a case for the simulation. The methodology intends to support decisions not only in the design phases, but also in the post-construction ones. Furthermore, it opens to potential applications in reinforced concrete infrastructures’ stock, which is approaching, as a considerable portion of the building stock, its end-of-life stage.
Bioeconomy Transformation Strategies Worldwide Require Stronger Focus on Entrepreneurship
Authors: Kuckertz Andreas
Published: April 2020

The number of governments worldwide embracing the vision of a sustainable bioeconomy is constantly rising. One factor facilitating the transformation of economies to such sustainable bioeconomies will be entrepreneurial activity. Hence, I analyze how available bioeconomy strategies account for the role of entrepreneurship in driving the bioeconomy transformation. That analysis indicates that the majority of existing bioeconomy strategies account for the transformative potential of entrepreneurship but remain ineffective with respect to achieving their goals. I consequently suggest devising entrepreneurship substrategies of bioeconomy strategies that are holistic, dedicated, and based on a clear causal rationale.
Productivity Evaluation of Tourism and Culture for Sustainable Economic Development: Analyzing South Korea’s Metropolitan Regions
Authors: Joun Hyo-Jae , Kim Hany
Published: April 2020

We analyzed the productivity of tourism- and culture-related economic activity in South Korea, adopting the Malmquist productivity index based on data envelopment analysis. We examined whether the productivity of tourism efficiently attracts financial investment. We used various objective indicators as the input and output variables of 16 metropolitan regions in South Korea between 2013 and 2018. To effectively understand the productivity of regions, the 16 metropolitan regions were categorized into four groups based on the ratio of financial independence and rate of city region, and regions were characterized as urbanized, traditional metropolitan, industrialized, or less developed. The findings reveal that the tourism industry in relatively less urbanized regions is more productive. Compared with other industries, public pre-investment and private investment strategies specific to tourism may yield more efficient results in terms of total production and employment. In other words, tourism may constitute a gateway to economic sustainability in less developed regions through the revitalization and/or balanced development of local structures.
Is Foreign Exchange Intervention a Panacea in Diversified Circumstances? The Perspectives of Asymmetric Effects
Authors: Wang Wenbo , Le Dieu Thanh , Park Hail
Published: April 2020

Owing to the country’s heavy reliance on exports, the role of foreign exchange intervention in South Korea’s economic development is self-evident. The effectiveness of the intervention is what we are concerned with in this paper. Recently, a growing body of literature has engaged in exploring the asymmetric effects of foreign exchange intervention both theoretically and empirically. Against this background, we employ a threshold vector autoregression (TVAR) model in parallel with its generalized impulse response functions (GIRFs) to show that there are asymmetric effects of the Bank of Korea (BOK)-led interventions regardless of the volatility regimes.
A Novel Hybrid Deep Neural Network Model to Predict the Refrigerant Charge Amount of Heat Pumps
Authors: Hwang Jun Kwon , Duhirwe Patrick Nzivugira , Yun Geun Young , Lee Sukho , Seo Hyeongjoon , Kim Inhan , Santamouris Mat
Published: April 2020

Improper refrigerant charge amount (RCA) is a recurring fault in electric heat pump (EHP) systems. Because EHP systems show their best performance at optimum charge, predicting the RCA is important. There has been considerable development of data-driven techniques for predicting RCA; however, the current data-driven approaches for estimating RCA suffer from poor generalization and overfitting. This study presents a hybrid deep neural network (DNN) model that combines both a basic DNN model and a thermodynamic model to counter the abovementioned challenges of existing data-driven approaches. The data for designing models were collected from two EHP systems with different specifications, which were used for the training and testing of models. In addition to the data obtained using the basic DNN model, the hybrid DNN model uses the thermodynamic properties as a thermodynamic model. The testing results show that the hybrid DNN model has a prediction performance of 93%, which is 21% higher than that of the basic DNN model. Furthermore, for model training and model testing, the hybrid DNN model has a 6% prediction performance difference, indicating its reliable generalization capabilities. To summarize, the hybrid DNN model improves data-driven approaches and can be used for designing efficient and energy-saving EHP systems.
Smart City Development in Taiwan: From the Perspective of the Information Security Policy
Authors: Wu Yung Chang , Sun Rui , Wu Yenchun Jim
Published: April 2020

A smart city is developed through the Internet of Things (IoT), cloud computing, big data, mobile Internet, and other new generation technologies regarding information and communication, and data resources in various fields are integrated and applied. The issue of information security in the network era is the strategic focus, as well as the focus of people’s attention, during Taiwan’s smart city construction. Information security policies are the information security guidelines for organizations, and are key to the organization’s information security performance; moreover, such policies show the organization’s support and commitment to the information security of smart cities. This paper discusses the model of information security policy in Taiwan’s smart cities, uses Path Analysis to explore the characteristics of information security policy in smart cities, and examines the relationship between the formulation, implementation, maintenance, and effectiveness of information security policies. Furthermore, this study examines the impact on the effectiveness of organizational information security policies and information security performance from the following aspects: The length of information security policy publication time, policy review, policy advocacy, employee compliance, fair law enforcement, etc., which are all concrete manifestations of the formulation, implementation, and maintenance of information security policy models. Through a questionnaire survey, the correlation between various assumptions, as well as the relationship between organizational information security characteristics, information security policies, and the effectiveness of information security, are verified one by one during the implementation of information security policies. Finally, conclusions and implications are put forward.
Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
Authors: Kim GwanSeon , Nemati Mehdi , Buck Steven , Pates Nicholas , Mark Tyler
Published: April 2020

This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.
Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka
Authors: Dissanayake DMSLB , Morimoto Takehiro , Murayama Yuji , Ranagalage Manjula , Perera ENC
Published: April 2020

The blooming of urban expansion has led to the improvement of urban life, but some of the negative externalities have affected the life quality of urban dwellers, both directly and indirectly. As a result of this, research related to the quality of life has gained much attention among multidisciplinary researchers around the world. A number of attempts have been made by previous researchers to identify, assess, quantify, and map quality of life or well-being under various kinds of perspectives. The objectives of this research were to create a life quality index (LQI) and identify the spatial distribution pattern of LQI in Kandy City, Sri Lanka. Multiple factors were decomposed, a hierarchy was constructed by the multi-criteria decision making (MCDM) method, and 13 factors were selected under two main criteria—environmental and socioeconomic. Pairwise comparison matrices were created, and the weight of each factor was determined by the analytic hierarchy process (AHP). Finally, gradient analysis was employed to examine the spatial distribution pattern of LQI from the city center to the periphery. The results show that socioeconomic factors affect the quality of life more strongly than environmental factors, and the most significant factor is transportation. The highest life quality zones (26% of the total area) were distributed around the city center, while the lowest zones represented only 9% of the whole area. As shown in the gradient analysis, more than 50% of the land in the first five kilometers from the city center comes under the highest life quality zone. This research will provide guidance for the residents and respective administrative bodies to make Kandy City a livable city. It the constructed model can be applied to any geographical area by conducting necessary data calibration.
Revisiting Energy Demand Relationship: Theory and Empirical Application
Authors: Hasanov Fakhri J. , Mikayilov Jeyhun I.
Published: April 2020

In this paper, we revisit the theoretical framework for energy demand. We then use this theoretical framework to empirically model the Saudi Arabian industrial electricity demand. We show, in the case of Saudi Arabian data, that imposing parsimonious energy demand specification on data without testing relevant assumptions can lead to biased estimations and noticeably poor approximations, while imposing general energy demand specification without accounting for the data properties can lead to redundant estimations and lower approximation than what could be obtained otherwise. Combining the theory with the data can provide unbiased and irredundant estimations with high levels of approximations. Hence, this paper recommends, based on the empirical findings, that a better strategy would be the combination of theoretical coherence with data coherence in the General to Specific Modeling (GtSM) framework for the empirical analyses of energy demand.