bluuebunny/crossref_metadata_2025 huggingface dataset:
Long Time-Series Mapping and Change Detection of Coastal Zone Land Use Based on Google Earth Engine and Multi-Source Data Fusion
Authors: Chen Dong , Wang Yafei , Shen Zhenyu , Liao Jinfeng , Chen Jiezhi , Sun Shaobo
Published: December 2021

Human activities along with climate change have unsustainably changed the land use in coastal zones. This has increased demands and challenges in mapping and change detection of coastal zone land use over long-term periods. Taking the Bohai rim coastal area of China as an example, in this study we proposed a method for the long time-series mapping and change detection of coastal zone land use based on Google Earth Engine (GEE) and multi-source data fusion. To fully consider the characteristics of the coastal zone, we established a land-use function classification system, consisting of cropland, coastal aquaculture ponds (saltern), urban land, rural settlement, other construction lands, forest, grassland, seawater, inland fresh-waters, tidal flats, and unused land. We then applied the random forest algorithm, the optimal classification method using spatial morphology and temporal change logic to map the long-term annual time series and detect changes in the Bohai rim coastal area from 1987 to 2020. Validation shows an overall acceptable average accuracy of 82.30% (76.70–85.60%). Results show that cropland in this region decreased sharply from 1987 (53.97%) to 2020 (37.41%). The lost cropland was mainly transformed into rural settlements, cities, and construction land (port infrastructure). We observed a continuous increase in the reclamation with a stable increase at the beginning followed by a rapid increase from 2003 and a stable intermediate level increase from 2013. We also observed a significant increase in coastal aquaculture ponds (saltern) starting from 1995. Through this case study, we demonstrated the strength of the proposed methods for long time-series mapping and change detection for coastal zones, and these methods support the sustainable monitoring and management of the coastal zone.
Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia
Authors: Sari Inggit Lolita , Weston Christopher J. , Newnham Glenn J. , Volkova Liubov
Published: December 2021

Over the last 18 years, Indonesia has experienced significant deforestation due to the expansion of oil palm and rubber plantations. Accurate land cover maps are essential for policymakers to track and manage land change to support sustainable forest management and investment decisions. An automatic digital processing (ADP) method is currently used to develop land cover change maps for Indonesia, based on optical imaging (Landsat). Such maps produce only forest and non-forest classes, and often oil palm and rubber plantations are misclassified as native forests. To improve accuracy of these land cover maps, this study developed oil palm and rubber plantation discrimination indices using the integration of Landsat-8 and synthetic aperture radar Sentinel-1 images. Sentinel-1 VH and VV difference (>7.5 dB) and VH backscatter intensity were used to discriminate oil palm plantations. A combination of Landsat-8 NDVI, NDMI with Sentinel-1 VV and VH were used to discriminate rubber plantations. The improved map produced four land cover classes: native forest, oil palm plantation, rubber plantation, and non-forest. High-resolution SPOT 6/7 imagery and ground truth data were used for validation of the new classified maps. The map had an overall accuracy of 92%; producer’s accuracy for all classes was higher than 90%, except for rubber (65%), and user’s accuracy was over 80% for all classes. These results demonstrate that indices developed from a combination of optical and radar images can improve our ability to discriminate between native forest and oil palm and rubber plantations in the tropics. The new mapping method will help to support Indonesia’s national forest monitoring system and inform monitoring of plantation expansion.
Mineralogical Mapping with Accurately Corrected Shortwave Infrared Hyperspectral Data Acquired Obliquely from UAVs
Authors: Thiele Samuel T. , Bnoulkacem Zakaria , Lorenz Sandra , Bordenave Aurélien , Menegoni Niccolò , Madriz Yuleika , Dujoncquoy Emmanuel , Gloaguen Richard , Kenter Jeroen
Published: December 2021

While uncrewed aerial vehicles are routinely used as platforms for hyperspectral sensors, their application is mostly confined to nadir imaging orientations. Oblique hyperspectral imaging has been impeded by the absence of robust registration and correction protocols, which are essential to extract accurate information. These corrections are especially important for detecting the typically small spectral features produced by minerals, and for infrared data acquired using pushbroom sensors. The complex movements of unstable platforms (such as UAVs) require rigorous geometric and radiometric corrections, especially in the rugged terrain often encountered for geological applications. In this contribution we propose a novel correction methodology, and associated toolbox, dedicated to the accurate production of hyperspectral data acquired by UAVs, without any restriction concerning view angles or target geometry. We make these codes freely available to the community, and thus hope to trigger an increasing usage of hyperspectral data in Earth sciences, and demonstrate them with the production of, to our knowledge, the first fully corrected oblique SWIR drone-survey. This covers a vertical cliff in the Dolomites (Italy), and allowed us to distinguish distinct calcitic and dolomitic carbonate units, map the qualitative abundance of clay/mica minerals, and thus characterise seismic scale facies architecture.
The Effect of Urban Form on PM2.5 Concentration: Evidence from China’s 340 Prefecture-Level Cities
Authors: Liu Ying , He Lijie , Qin Wenmin , Lin Aiwen , Yang Yanzhao
Published: December 2021

Exploring how urban form affects the Particulate Matter 2.5 (PM2.5) concentration could help to find environmentally friendly urbanization. According to the definition of geography, this paper constructs a comprehensive urban form evaluation index system applicable to many aspects. Four urban form metrics, as well as road density and five control variables are selected. Based on 2015 data on China’s 340 prefecture-level cities, the spatial regression model and geographically weighted regression model were used to explore the relationship between the urban form evaluation index system and PM2.5 pollution. The main results show that the spatial distribution of PM2.5 in China follows an increasing trend from northwest to southeast. Urban form indicators such as AI, LPI, PLAND, LSI and road density were all significantly related to PM2.5 concentrations. More compact urban construction, lower fragmentation of urban land, and lower density of the road network are conducive factors for improving air quality conditions. In addition, affected by seasonal changes, the correlation between urban form and PM2.5 concentration in spring and winter is higher than that in summer and winter. This study confirmed that a reasonable urban planning strategies are very important for improving air quality.
A Lightweight Convolutional Neural Network Based on Channel Multi-Group Fusion for Remote Sensing Scene Classification
Authors: Shi Cuiping , Zhang Xinlei , Wang Liguo
Published: December 2021

With the development of remote sensing scene image classification, convolutional neural networks have become the most commonly used method in this field with their powerful feature extraction ability. In order to improve the classification performance of convolutional neural networks, many studies extract deeper features by increasing the depth and width of convolutional neural networks, which improves classification performance but also increases the complexity of the model. To solve this problem, a lightweight convolutional neural network based on channel multi-group fusion (LCNN-CMGF) is presented. For the proposed LCNN-CMGF method, a three-branch downsampling structure was designed to extract shallow features from remote sensing images. In the deep layer of the network, the channel multi-group fusion structure is used to extract the abstract semantic features of remote sensing scene images. The structure solves the problem of lack of information exchange between groups caused by group convolution through channel fusion of adjacent features. The four most commonly used remote sensing scene datasets, UCM21, RSSCN7, AID and NWPU45, were used to carry out a variety of experiments in this paper. The experimental results under the conditions of four datasets and multiple training ratios show that the proposed LCNN-CMGF method has more significant performance advantages than the compared advanced method.
Spatial and Temporal Distributions of Ionospheric Irregularities Derived from Regional and Global ROTI Maps
Authors: Nguyen Chinh Thai , Oluwadare Seun Temitope , Le Nhung Thi , Alizadeh Mahdi , Wickert Jens , Schuh Harald
Published: December 2021

Major advancements in the monitoring of both the occurrence and impacts of space weather can be made by evaluating the occurrence and distribution of ionospheric disturbances. Previous studies have shown that the fluctuations in total electron content (TEC) values estimated from Global Navigation Satellite System (GNSS) observations clearly exhibit the intensity levels of ionospheric irregularities, which vary continuously in both time and space. The duration and intensity of perturbations depend on the geographic location. They are also dependent on the physical activities of the Sun, the Earth’s magnetic activities, as well as the process of transferring energy from the Sun to the Earth. The aim of this study is to establish ionospheric irregularity maps using ROTI (rate of TEC index) values derived from conventional dual-frequency GNSS measurements (30-s interval). The research areas are located in Southeast Asia (15°S–25°N latitude and 95°E–115°E longitude), which is heavily affected by ionospheric scintillations, as well as in other regions around the globe. The regional ROTI map of Southeast Asia clearly indicates that ionospheric disturbances in this region are dominantly concentrated around the two equatorial ionization anomaly (EIA) crests, occurring mainly during the evening hours. Meanwhile, the global ROTI maps reveal the spatial and temporal distributions of ionospheric scintillations. Within the equatorial region, South America is the most vulnerable area (22.6% of total irregularities), followed by West Africa (8.2%), Southeast Asia (4.7%), East Africa (4.1%), the Pacific (3.8%), and South Asia (2.3%). The generated maps show that the scintillation occurrence is low in the mid-latitude areas during the last solar cycle. In the polar regions, ionospheric irregularities occur at any time of the day. To compare ionospheric disturbances between regions, the Earth is divided into ten sectors and their irregularity coefficients are calculated accordingly. The quantification of the degrees of disturbance reveals that about 58 times more ionospheric irregularities are observed in South America than in the southern mid-latitudes (least affected region). The irregularity coefficients in order from largest to smallest are as follows: South America, 3.49; the Arctic, 1.94; West Africa, 1.77; Southeast Asia, 1.27; South Asia, 1.24; the Antarctic, 1.10; East Africa, 0.89; the Pacific, 0.32; northern mid-latitudes, 0.15; southern mid-latitudes, 0.06.
Livestock Informatics Toolkit: A Case Study in Visually Characterizing Complex Behavioral Patterns across Multiple Sensor Platforms, Using Novel Unsupervised Machine Learning and Information Theoretic Approaches
Authors: McVey Catherine , Hsieh Fushing , Manriquez Diego , Pinedo Pablo , Horback Kristina
Published: December 2021

Large and densely sampled sensor datasets can contain a range of complex stochastic structures that are difficult to accommodate in conventional linear models. This can confound attempts to build a more complete picture of an animal’s behavior by aggregating information across multiple asynchronous sensor platforms. The Livestock Informatics Toolkit (LIT) has been developed in R to better facilitate knowledge discovery of complex behavioral patterns across Precision Livestock Farming (PLF) data streams using novel unsupervised machine learning and information theoretic approaches. The utility of this analytical pipeline is demonstrated using data from a 6-month feed trial conducted on a closed herd of 185 mix-parity organic dairy cows. Insights into the tradeoffs between behaviors in time budgets acquired from ear tag accelerometer records were improved by augmenting conventional hierarchical clustering techniques with a novel simulation-based approach designed to mimic the complex error structures of sensor data. These simulations were then repurposed to compress the information in this data stream into robust empirically-determined encodings using a novel pruning algorithm. Nonparametric and semiparametric tests using mutual and pointwise information subsequently revealed complex nonlinear associations between encodings of overall time budgets and the order that cows entered the parlor to be milked.
Unsupervised Event Graph Representation and Similarity Learning on Biomedical Literature
Authors: Frisoni Giacomo , Moro Gianluca , Carlassare Giulio , Carbonaro Antonella
Published: December 2021

The automatic extraction of biomedical events from the scientific literature has drawn keen interest in the last several years, recognizing complex and semantically rich graphical interactions otherwise buried in texts. However, very few works revolve around learning embeddings or similarity metrics for event graphs. This gap leaves biological relations unlinked and prevents the application of machine learning techniques to promote discoveries. Taking advantage of recent deep graph kernel solutions and pre-trained language models, we propose Deep Divergence Event Graph Kernels (DDEGK), an unsupervised inductive method to map events into low-dimensional vectors, preserving their structural and semantic similarities. Unlike most other systems, DDEGK operates at a graph level and does not require task-specific labels, feature engineering, or known correspondences between nodes. To this end, our solution compares events against a small set of anchor ones, trains cross-graph attention networks for drawing pairwise alignments (bolstering interpretability), and employs transformer-based models to encode continuous attributes. Extensive experiments have been done on nine biomedical datasets. We show that our learned event representations can be effectively employed in tasks such as graph classification, clustering, and visualization, also facilitating downstream semantic textual similarity. Empirical results demonstrate that DDEGK significantly outperforms other state-of-the-art methods.
Ultra-Widefield Fluorescein Angiography Image Brightness Compensation Based on Geometrical Features
Authors: Więcławek Wojciech , Danch-Wierzchowska Marta , Rudzki Marcin , Sędziak-Marcinek Bogumiła , Teper Slawomir Jan
Published: December 2021

Ultra-widefield fluorescein angiography (UWFA) is an emerging imaging modality used to characterise pathologies in the retinal vasculature, such as microaneurysms (MAs) and vascular leakages. Despite its potential value for diagnosis and disease screening, objective quantitative assessment of retinal pathologies by UWFA is currently limited because laborious manual processing is required. In this report, we describe a geometrical method for uneven brightness compensation inherent to UWFA imaging technique. The correction function is based on the geometrical eyeball shape, therefore it is fully automated and depends only on pixel distance from the center of the imaged retina. The method’s performance was assessed on a database containing 256 UWFA images with the use of several image quality measures that show the correction method improves image quality. The method is also compared to the commonly used CLAHE approach and was also employed in a pilot study for vascular segmentation, giving a noticeable improvement in segmentation results. Therefore, the method can be used as an image preprocessing step in retinal UWFA image analysis.
Estimation of Travel Demand for Bangkok–Chiang Mai Hyperloop Using Traveler Surveys
Authors: Agrawal Paras , Pravinvongvuth Surachet
Published: December 2021

Hyperloop, projected as fast and efficient, and envisaged as the future of high-speed transportation, does not have much published information about its demand estimation. This paper aims to estimate the willingness of air and car passengers to shift to hyperloop. A nested logit model was used to analyze stated preference data gathered from the air and car travelers along the Bangkok–Chiang Mai sector in Thailand. The variables contributing the most to the modal shift towards hyperloop are total travel cost, total travel time, monthly income, gender, education level, bearer of trip expenses, and number of trips in the last 6 months and duration of stay at the destination. The highest value of elasticity for hyperloop is obtained for the total travel cost followed by total travel time and monthly income. It is concluded that hyperloop will be the predominant mode of transportation between the Bangkok–Chiang Mai sectors with a modal share of almost 50% by the year 2025. Survey results also revealed that the preferences of the passengers in order of priorities for long distance travel are comfort, low travel cost, less travel time, safety, high frequency of travel mode and low CO2 emission. The main contribution of this paper is to provide an insight on factors that may contribute towards a possible shift in mode from car and air to hyperloop. The study will be beneficial to policy makers in developing a strategy for a more efficient mass transportation system using new and emerging technologies.
Hybrid Approach to Corporate Sustainability Performance in Indonesia’s Cement Industry
Authors: Wang Ching-Hsin , Chen Yi-Chun , Sulistiawan Jovi , Bui Tat-Dat , Tseng Ming-Lang
Published: December 2021

This study aimed to create a solid framework for decision-making in Indonesia’s cement industry, emphasizing those factors which bring about the most impactful results. The framework was developed using the fuzzy Delphi method, the fuzzy decision-making trial and evaluation laboratory, and a fuzzy Kano model. This study builds a hierarchical structure to approach the impact of corporate sustainability performance. We classify important factors into causes or effects and further identify those factors which are critical to improving the performance of Indonesia’s cement industry. Although corporate sustainability performance is a crucial topic in today’s business environment, sustainability strategies remain underrated in Indonesia. We confirm the validity of 19 factors within the following dimensions: environmental impact, social sustainability, economic gain, technological feasibility, and institutional compliance. The sub-dimensions of community interest, risk-taking ability, and regulatory compliance were identified as causes of perceived risks and benefits. In contrast, the following factors were identified as critical to improving corporate sustainability performance: renewable energy resources, contributions to charity, the perception of management regarding technology as a differentiator, and firm readiness to collaborate with high-tech companies.
Applications of Biochar and Modified Biochar in Heavy Metal Contaminated Soil: A Descriptive Review
Authors: Liang Meina , Lu Lin , He Huijun , Li Jingxi , Zhu Zongqiang , Zhu Yinian
Published: December 2021

Given that the problem of contaminated soil continues to grow, the development of effective control and remediation measures has become imperative, especially for heavy-metal-contaminated soil. Biochar and modified biochar are eco-friendly and cost-effective remediation materials that are widely used in the remediation of contaminated soil. This review provides an overview of the different raw materials used in the preparation of biochar as well as the modification of biochar using various synthesis methods, highlighting their differences and providing recommendations for biochar and modified biochar as applied toward ameliorating pollution in soil contaminated by heavy metals. We also explore the effects of the physicochemical properties of raw materials, pyrolysis temperature, additives, and modification methods on the properties of the resulting biochar and modified biochar, and systematically present the types of soil and operating factors for repair. Moreover, the mechanisms involved in remediation of heavy-metal-contaminated soil by biochar and modified biochar are outlined in detail, and include adsorption, complexation, precipitation, ion exchange, and electrostatic attractions. Finally, the corresponding monitoring technologies after remediation are illustrated. Future directions for studies on biochar and modified biochar in the remediation of contaminated soil are also proposed to support the development of green environmental protection materials, simple preparation methods, and effective follow-up monitoring techniques.
BEPU Analysis in LBLOCA Safety Review Calculation
Authors: Sun Wei , Xu Chao , Wang Yi-Zhen , Qiu Sui-Zheng , Liu Yu-Sheng , Fu Hao
Published: December 2021

Deterministic safety analysis (DSA) is essential for nuclear power plant licensing. The conservative method followed CFR50 Appendix K, which will lead to a large margin. As one of the DSA methodologies, best estimate plus uncertainty (BEPU) generates more realistic results that can be used in the license application of nuclear power plants (NPPs). However, uncertainty evaluation of parameters is needed in BEPU. In this article, the safety regulatory focuses on the large break loss of coolant accident (LBLOCA) of an advanced PWR. The BEPU analysis is mainly performed by TRACE V5.0 patch 4 code, and the uncertainty analysis is conducted based on DAKOTA code. For correlation coefficients analysis, the sample size is enlarged reasonably. According to the results, this NPP meets the acceptance criteria effectively in LBLOCA with enough margin. By statistic assessment, the set of PCTs calculated has typical normal distribution characters. Based on BEPU, the uncertainties of parameters are studied. Additionally, the influence of sample size on the correlation of parameters is considered too. It could be seen that more samples could permit a more accurate estimation for Spearman partial correlation coefficient (abbreviated as SPCC). The conclusions of this article can provide technical support for the subsequent review of the safety analysis report and the design changes of NPPs.
Can Post-Vaccine ‘Vaxication’ Rejuvenate Global Tourism? Nexus between COVID-19 Branded Destination Safety, Travel Shaming, Incentives and the Rise of Vaxication Travel
Authors: Zaman Umer , Aktan Murat , Anjam Mahwish , Agrusa Jerome , Khwaja Muddasar Ghani , Farías Pablo
Published: December 2021

Vaxication (i.e., post-vaccination travel) and branding destinations for COVID-19 safety have emerged as the cornerstones to fully rebound global tourism. Numerous destination brands are now stimulating tourism demand through realigned travel incentives specifically for fully vaccinated travelers. However, there is growing fear and incidents of travel shaming across destinations, especially due to the recent outbreaks of the highly contagious COVID-19 ‘delta and omicron’ variants. Addressing this critical research gap, the present study makes pioneering efforts to empirically examine the effects of COVID-19 branded destination safety (CBDS) on vaxication intentions, under the moderating influence of travel shaming and travel incentives. Drawing on study data from 560 fully-vaccinated residents from Hawaii, United States and structural equation modeling (SEM) with Mplus, the evidence suggests that the positive impact of CBDS on vaxication intention can be further strengthened by travel incentives, or weakened when travel shaming picks up more momentum. Besides the validation of newly developed scales, the study offers strategic insights based on dominant theories (e.g., theory of planned behavior and protection motivation theory) to interpret the changing tourism demand, and to transform the emerging challenges into opportunities through and beyond the pandemic.
Comment on Alam et al. Numerical Simulation of Homogeneous–Heterogeneous Reactions through a Hybrid Nanofluid Flowing over a Rotating Disc for Solar Heating Applications. Sustainability 2021, 13, 8289
Authors: Awad Mohamed M.
Published: December 2021

Alam et al. [...]
Public Perception of Tourism Cities before and during the COVID-19 Pandemic through the Lens of User-Generated Content
Authors: Chen Yulin
Published: December 2021

The COVID-19 pandemic (coronavirus disease of 2019) sent the world into disarray and devastated the global tourism economy. In 2020 alone, the number of international tourists dropped by roughly 1.1 billion. This study examines user-generated content (UGC) on social media to elucidate the shift in people’s perceptions of popular tourism cities from before the pandemic to during the pandemic. This paper analyzes the characteristics of the cues in tourism-city-related UGC (particularly those related to the pandemic) and identifies the cues that resonate most with the public. This paper collected the data using Instagram’s application programing interface and then sorted the UGC based on content, type, time, likes, share, and comments. Between 1 January 2019 and 31 December 2019, it collected a total of 207,752 pre-pandemic posts and 173,131 peri-pandemic posts. The findings reveal that, during the pandemic, the interactivity of city-related UGC dropped, and only pandemic-related keywords gained public attention. By comparison, pre-pandemic positive posts mentioned local features and contained calls to action that were generally well-received. The findings also validate that UGC effectively reflects and enhances overall public perceptions, suggesting that, in a future which is forced to co-exist with SARS-CoV-2 in the long term, it is important to understand the positive and negative influences of UGC on tourism cities.
Do Cross-Latitude and Local Studies Give Similar Predictions of Phytoplankton Responses to Warming? An Analysis of Monitoring Data from 504 Danish Lakes
Authors: Jeppesen Erik , Johansson Liselotte S. , Tserenpil Sh , Søndergaard Martin , Lauridsen Torben L. , Andersen Per
Published: December 2021

Cross-latitude studies on lakes have a potential to predict how global warming may cause major changes in phytoplankton biomass and composition, e.g., the development of favourable conditions for cyanobacteria dominance. However, results from these studies may be influenced by biogeographical factors, and the conclusions may, therefore, not hold when considering local response patterns. We used monthly monitoring data from 504 lakes in Denmark—a small and homogeneous geographical region—to establish empirical relationships between key phytoplankton groups and a set of explanatory variables including total phosphorus (TP), total nitrogen (TN), lake mean depth (DEP) and water temperature (TEMP). All variables had strong effects on phytoplankton biomass and composition, but their contributions varied over the seasons, with TEMP being particularly important in June–October. We found dominance of cyanobacteria in terms of biomass and also an increase in dinophytes biomass at higher TEMP, while diatoms and chlorophytes became less important. In May, however, the TEMP effect on total phytoplankton biomass was negative, likely reflecting intensified zooplankton grazing. Our results suggest that biogeographical effects are of minor importance for the response patterns of phytoplankton to temperature and that substantial concentration reductions of TN and TP are needed in eutrophic lakes to counteract the effect of the climate change-induced increase in TEMP.
The Cloud-Enabled Architecture of the Clinical Data Repository in Poland
Authors: Augustyn Dariusz R. , Wyciślik Łukasz , Sojka Mateusz
Published: December 2021

In this article, the authors, using information-systems modeling techniques, and considering current national legal regulations, present the cloud-enabled architecture of a clinical data repository. The patient’s medical record is an important carrier of information necessary for accurate diagnosis and selection of the correct treatment process. Therefore, it is not surprising that since the beginning of the development of computer technologies, databases have been built to enable the management of a patient’s medical records. These systems were most-often deployed locally at individual healthcare units, which carried certain limitations both in terms of the security and availability of the stored information, and the possibility of exchanging it with other clinics. However, recent developments in the standardization of medical information exchange in Poland, together with the revolution in cloud computing, have opened up completely new perspectives for clinical-data-repository implementations helping to make them far more sustainable. Although, the practical aspects of implementing clinical-documentation repositories are studied both in forums of European countries and also around the world; so far, no similar research was conducted with respect to Poland. This study tries to fill that gap by proposing a flexible multi-variant cloud-enabled architecture of the system providing the services of a clinical-data repository. The goal of the work was to propose such a system architecture that allows having a system that is either cloud-agnostic, that uses specifically selected cloud services, or that is even deployable locally. Thanks to the use of cloud computing services, the implemented system is characterized by high availability, scalability, and the possibility of exchanging data between medical institutions, which enables the improvement in the quality of medical processes for the whole Polish population.
Going beyond Cryptocurrencies: The Social Representation of Blockchain
Authors: Joia Luiz Antonio , Vieira Juliana Aparecida Pinto
Published: December 2021

This study investigates the social representation of Blockchain from the perspective of professionals in Brazil, herein considered as a proxy for emerging markets, and then compares the results found with the existing academic literature on the concept of Blockchain. To do that, the social representation theory was applied, operationalized through the words evocation technique. Security, bitcoin and decentralization were the categories located in the central nucleus of the social representation of Blockchain, while innovation, data, network, cryptocurrency, and technology were the categories located in the peripheral system. Based on the results obtained, there was a perceived strong association of Blockchain with bitcoin, one of its applications, and a dissonance between the existing academic literature and the perception of Brazilian professionals about the concept of Blockchain, as the latter is a privilege of the technical and operational issues of Blockchain to the detriment of its strategic potential. This dissonance can cause Blockchain initiatives to have results below expectations. Finally, Brazilian professionals did not realize the potential for inclusion of Blockchain in an emerging market such as Brazil and did not notice the need and relevance of a specific legal governance for Blockchain, an issue also forgotten by academia.
Towards Good Governance on Dual-Use Biotechnology for Global Sustainable Development
Authors: Xue Yang , Yu Hanzhi , Qin Geng
Published: December 2021

Dual-use biotechnology faces the risks of availability, novel biological agents, knowledge, normative, and other dual-use risks. If left unchecked, these may destroy human living conditions and social order. Despite the benefits of dual-use technology, good governance is needed to mitigate its risks. The predicaments facing all governments in managing the dual-use risks of biotechnology deserve special attention. On the one hand, the information asymmetry risk of dual-use biotechnology prevents the traditional self-governance model in the field of biotechnology from playing its role. On the other hand, top-down public regulation often lags behind technological iteration due to the difficulty of predicting the human-made risks of dual-use biotechnology. Therefore, we argue that governance of the dual-use risks of biotechnology should avoid the traditional bottom-up or top-down modes. We suggest the governance for dual-use biotechnology could be improved if the four-stage experimentalist governance model is followed. The first stage is to achieve consensus on a broad governance framework with open-ended principles. The second stage is for countries to take action based on local conditions and the open-ended framework. The third stage is to establish a dynamic consultation mechanism for transnational information sharing and action review. The fourth and final stage is to evaluate and revise the global governance framework.
A Study on Transboundary Marine Governance of Floating Marine Debris—Taking Kinmen–Xiamen Waters between China and Taiwan as an Example
Authors: Kao Jui-Chung , Cho Cheng-Chung , Kao Rui-Hsin
Published: December 2021

Mainland China’s economy has been developing rapidly. Unfortunately, it has led to an increase in municipal and industrial waste, including in Xiamen, in which is has greatly increased. Kinmen is located outside the estuary of the Jiulong River in Fujian, Mainland China, opposite to Xiamen Bay. Whenever there is heavy rainfall, the waste that flows along the Jiulong River is incredible. Kinmen unavoidably has to bear the invasion of floating marine debris due to the effect of ocean currents, tides and monsoons. It does not only pollute the Kinmen sea area, but it also affects the scenery of the beaches in Kinmen. Therefore, this study aimed to explore the data of Kinmen and Xiamen governments regarding the cleaning of floating marine debris, and the differences in distribution areas according to the monsoon, ocean current and tides. In-depth interviews, field investigation, and collection of expert opinions were applied in order to determine the research implication. The results of this study provide information on the marine issues encountered in the governance of the countries surrounding the sea. The study suggests that the transboundary marine governance mechanism should be established in order to effectively solve the problem of floating marine debris in Kinmen–Xiamen Waters. For the welfare of the people, it is expected that the governments of Mainland China and Taiwan will uphold the principle of “pragmatism and reciprocity” by working together to maintain the marine environment in Kinmen–Xiamen waters.
Role of Augmented Reality in Changing Consumer Behavior and Decision Making: Case of Pakistan
Authors: Kazmi Syed Hasnain Alam , Ahmed Rizwan Raheem , Soomro Kamran Ahmed , Hashem E Alharthi Rami , Akhtar Hameed , Parmar Vishnu
Published: December 2021

Marketers and advertisers ignore new technology and diverse marketing tactics when attempting to increase product exposure, customer engagement, customer behavior and buying intention in fashion accessory marketplaces in developing countries. This research sought to discover how the Augmented Reality (AR) experience influenced consumer behavior, buying intention and pleasure when purchasing a fashion item in developing countries. This study employs positivist ideas to investigate the connections between various factors, believing that reality is unwavering, stable, and static. Experiential marketing following stimulus exposure will gather cross-sectional data. The undertaken study has developed proper experimental design (within group) from business innovation models, for instance, uses and gratification and user experience models. User experience is disclosed by its four defining characteristics: hedonic quality (identification and simulation), aesthetic quality, and pragmatic quality. After encountering an enhanced user experience, users have a more favorable attitude about purchasing; in contrast, pleasure from using the application directly impacts buying intention. It was also shown that knowledge of AR apps impacts user experience and attitude. The novelty of this research is multifarious, for instance, the smart lab was used as a marketing technology to explore a virtual mirror of the Ray-Ban products. Secondly, the augmented reality experiential marketing activities have been developed by the developers as bearing in mind the four different aspects of the user experience—haptic, hedonic, aesthetic, and pragmatic. It should be functional, simple to learn and use, symmetrical, pleasant, and appealing, while fulfilling the unconscious emotional elements of a customer’s purchase. The research is the first known study in Pakistan to evaluate the influence of augmented reality on consumer proficiency and its consequent effects on attitude and satisfaction for fashion accessory brands. The research also advances the notion that application familiarity is the most important moderator between attitude and an augmented reality-enriched user experience, contradicting the prior studies, which focus on gender and age. This research has important theoretical implications for future researchers, who may wish to replicate the proposed final model in developed and developing countries’ fashion brands. This research also has imperative managerial implications for brand managers and marketing managers, who could include the recommendations of this study in their marketing strategies.
The Spatial Effect of Shared Mobility on Urban Traffic Congestion: Evidence from Chinese Cities
Authors: Li Jiachen , Ma Mengqing , Xia Xin , Ren Wenhui
Published: December 2021

This paper explores the spatial spillover effect of shared mobility on urban traffic congestion by constructing spatial econometric models. Based on panel data of 94 Chinese cities from 2016 to 2019, this study analyses the spatial correlation of shared mobility enterprise layout and geographical correlation of urban transport infrastructure and examines their influence mechanism. From the perspective of geographic spatial distribution, congestion has positive spatial correlation among Chinese cities, and it has different directions and centripetal forces across regions. The shared mobility enterprises in a region have same direction distribution with traffic congestion, but the centripetal forces of the aggregation effect are different. The econometric results include the fact that bike-sharing has reduced congestion significantly, but the overall impact of car-sharing is not clear. Neither bike-sharing nor car-sharing can offset the traffic congestion caused by economic activities and income growth. From the perspective of spillover effects, congestion has been influenced by bike-sharing, economic development, population, and public passengers in surrounding areas. In terms of spatial heterogeneity, bike-sharing relieves congestion in the Pearl River Delta region while having no significant effect in other regions. Meanwhile, car-sharing has aggravated congestion in the Yangtze River Delta but eased traffic jams in the Pearl River Delta.
Indoor Environmental Quality Survey in Research Institute: A Floor-by-Floor Analysis
Authors: Lee Jong-Won , Kim Deuk-Woo , Lee Seung-Eon , Jeong Jae-Weon
Published: December 2021

Comprehensively monitoring indoor environmental quality (IEQ) parameters and their dynamic relations is essential to ensure improved productivity and a healthy environment for building occupants. Although IEQ significantly influences working efficiency, studies addressing this aspect with researchers in institutes as the focal point are limited. Thus, this study employed drill-down analyses, such as floor-by-floor and building-by-building examinations and used an occupant IEQ survey approach to evaluate working conditions in research buildings. This study systematically and objectively assessed IEQ using the Korea building occupant survey system. The results indicate that acoustic qualities affect the work productivity and satisfaction of the building occupants. The floor-by-floor analysis is necessary to identify IEQ factors and the reasons for the satisfaction of occupants. Additionally, it is important to improve the user-friendliness of the system, implement frequent survey distribution systems, and empirically analyze data associations among building, spatial, and demographical characteristics.
Relating Knowledge and Perception of Sustainable Landscape Practices to the Adoption Intention of Environmentally Friendly Landscapes
Authors: Zhang Xumin , Khachatryan Hayk , Knuth Melinda
Published: December 2021

The influence of traditional residential landscapes on humans and the environment has provoked a discussion on maintaining landscapes in a sustainable way and conserving water resources. Traditional American landscapes require water-intensive management. Previous research has discussed potential negative impacts on the environment from prevalent improper landscaping maintenance techniques. To mitigate long-term consequences, sustainable landscape management programs aim at protecting the environment from harmful inputs and conserving water. Among alternative practices, converting fully turfgrass lawns to sustainable landscapes is recommended. The Florida Friendly Landscaping (FFLTM) initiative is one such program designed to minimize negative impacts while maintaining and improving landscapes’ aesthetic characteristics. Although technological advancements in lawn care services have rapidly developed in the past few decades (e.g., smart irrigation systems), the level of homeowners’ knowledge and perceptions regarding sustainable practices are still at the forefront of potential factors that influence the widespread adoption of sustainable lawn management. Relatively few studies have investigated how homeowners’ knowledge and perceptions of sustainable landscapes affect adoption decisions. This study adapted Ajzen’s theory of planned behavior as a framework to examine how individuals’ knowledge and perceptions of sustainable landscapes influence their adoption intention, and to predict their pro-environmental behavior. We found that homeowners’ knowledge about lawns and landscapes (more knowledgeable) is positively correlated with their sustainable landscape adoption intention. Additionally, homeowners’ perceptions of landscape conservation practices (more agreeable with sustainable landscape practices) are positively correlated with sustainable landscape adoption intentions. The implications for policymakers and water conservation programs are discussed.
Indoor Nanoparticle Characterization in Construction Waste Recycling Companies over Time
Authors: Pinto Diana , Neckel Alcindo , Dotto Guilherme L. , Adelodun Bashir
Published: December 2021

Building activity is a significant source of atmospheric contamination by ultrafine dust. Cognizant of this fact, those active in the use and recycling of construction materials must be aware of the risks associated with exposure to nanoparticles (NPs) and ultra-fine particles (UFPs), as well as the associated health impacts. This work analyzed NPs and UFPs generated in a small building-material recycling company using high-resolution electron microscopes and X-ray Diffraction. A self-made passive sampler (LSPS) that can obtain particulate samples without physical and morphological changes, especially where there is a suspension of particulate material, was used in this study. A total of 96 particulate samples, using the LSPS for three months in four seasons, were collected during the study. Thus, the dry deposition of the particles, which are considered highly harmful to human health, was found in each of the four seasons of the year. It is suggested that for future research, the toxicological evaluations of the particulates in the construction industry should be investigated through the consideration of measures to control and mitigate the health risks of workers regarding exposure to NPs and UFPs.
Promoting a Pro-Ecological View: The Effects of Art on Engineering Students’ Perceptions of the Environment
Authors: Paek Kyong-Mi , Kim Hyomin
Published: December 2021

In an effort to suggest an extended role that art could play in promoting a pro-ecological worldview, this study reviews a two-week artist-led workshop, organized as part of an undergraduate art course offered by a university specializing in engineering and the natural sciences. To explore the potential impact of studio work on engineering student perceptions, we collected data from multiple sources, including field notes, participant observations, outcomes of the group projects, and participants’ responses to studio work during the workshop. In particular, to provide educational implications, our review focused on the findings from post-project surveys collected through online questionnaires and in-person interviews. In order to make suggestions on art courses that are specifically designed to cultivate engineering students’ perceptions of the environment, we carried out online surveys based on the New Ecological Paradigm (NEP) scale. The results of the NEP-based surveys indicated that engineering students’ anti-anthropocentrism, rejection of human exceptionalism, and acknowledgement of the possibility of an eco-crisis were significantly correlated with a belief in public welfare. By comparison, respondents’ stronger public welfare beliefs were not associated with beliefs in limits to growth and the fragility of nature’s balance. This study responds to today’s complex socio-environmental issues by contributing to the discussion about the need to integrate interdisciplinary approaches into engineering education on environmental sustainability.
Is Green Credit a Good Tool to Achieve “Double Carbon” Goal? Based on Coupling Coordination Model and PVAR Model
Authors: Hu Yi , Zheng Jiayu
Published: December 2021

China attaches importance to the combination of credit policy and environmental protection, tries to use credit policy tools to protect ecology and pollution prevention, and prevent environmental credit risk. With the proposal of the goal of “carbon peak and carbon neutralisation” (“double carbon”), green credit is also regarded as an important policy tool to achieve this goal. Firstly, this paper selects the time series data of green credit at the national level from 2013 to 2019 according to the official statistics and evaluates the coupling and coordinated development of credit system and environmental system based on the coupling coordination model. The results show that the two systems show well-coordinated development, but the interaction has annual fluctuations. Secondly, by calculating the provincial carbon emissions and green credit panel data from 2005 to 2019, the dynamic internal mechanism is analysed based on Panel Vector Autoregression (PVAR) model. It is found that green credit has a significant inhibitory effect on carbon emissions. The research results of this paper provide an overall evaluation of the quantity and quality of green credit for China’s banking industry. It also provides reasonable and effective support for green credit as a policy tool to promote realising the “double carbon” goal. In addition, China should maintain the consistency, stability and durability of green credit policy and continue to contribute to the low-carbon transformation of the economy and society.