bluuebunny/crossref_metadata_2025 huggingface dataset:
Soil Moisture Retrieval from the CyGNSS Data Based on a Bilinear Regression
Authors: Chen Sizhe , Yan Qingyun , Jin Shuanggen , Huang Weimin , Chen Tiexi , Jia Yan , Liu Shuci , Cao Qing
Published: April 2022

Soil moisture (SM) has normally been estimated based on a linear relationship between SM and the surface reflectivity (Γ) from the spaceborne Global Navigation Satellite System (GNSS)-Reflectometry, while it usually relies on inputs of SM data without considering vegetation optical depth (VOD/τ) effects. In this study, a new scheme is proposed for retrieving soil moisture from the Cyclone GNSS (CyGNSS) data. The variation of CyGNSS-derived ΔΓ is modeled as a function of both variations in SM and VOD (ΔSM and Δτ). For retrieving SM, ancillary τ data can be obtained from the Soil Moisture Active Passive (SMAP) mission. In addition to this option, a model for simulating Δτ is suggested as an alternative. Experimental evaluation is performed for the time span from August 2019 to July 2021. Excellent agreements between the final retrievals and referenced SMAP SM products are achieved for both training (1-year period) and test (1-year duration) sets. On the whole, overall correlation coefficients (r) of 0.97 and 0.95 and root-mean-square errors (RMSEs) of 0.024 and 0.028 cm3/cm3 are obtained based on models using the SMAP and simulated Δτ, respectively. The model without τ generates an r of 0.95 and an RMSE of 0.031 cm3/cm3. The efficiency and necessity of considering τ are thus confirmed by its enhancement based on correlation and RMSE against the one without τ, and the usefulness of approximating Δτ by sinusoidal functions is also validated. Influences of SM statistics in terms of mean and variance on the retrieval accuracy are evaluated. This work unveils the interaction between CyGNSS data, SM, and τ and demonstrates the feasibility of integrating the Δτ approximation function into a bilinear regression model to obtain SM results.
Comparative Study on Potential Landslide Identification with ALOS-2 and Sentinel-1A Data in Heavy Forest Reach, Upstream of the Jinsha River
Authors: Cao Chen , Zhu Kuanxing , Song Tianhao , Bai Ji , Zhang Wen , Chen Jianping , Song Shengyuan
Published: April 2022

Many SAR satellites such as the ALOS-2 satellite and Sentinel-1A satellite can be used in Interferometric Synthetic Aperture Radar (InSAR) to identify landslides. As their wavelengths are different, they can perform differently in the same area. In this study, we selected the alpine canyon heavy forest area of the Baishugong–Shangjiangxiang section of the Jinsha River with a strong uplift of faults and folds as the study area. The Small Baseline Subset (SBAS)–InSAR was used for landslide identification to compare the reliability and applicability of L-band ALOS-2 data and C-band Sentinel-1A data. In total, 13 potential landslides were identified, of which 12 potential landslides were identified by ALOS-2 data, two landslides were identified by Sentinel-1A data, and the Kongzhigong (KZG) landslide was identified by both datasets. Then, the field investigation was used to verify the identification results and analyze the genetic mechanism of four typical landslides. Both the Duila (DL) and KZG landslides are bedding slip, while the Jirenhe (JRH) and Maopo (MP) landslides are creep–pull failure. Then, the difference between ALOS-2 and Sentinel-1A data on KZG landslide was compared. A total of 35,961 deformation points on the KZG landslide were obtained using ALOS-2 data, which are relatively dense. Meanwhile, a total of 7715 deformation points were obtained by Sentinel-1A data, which are relatively scattered and seriously lacking, especially in areas with dense vegetation coverage. Comparing the advantages of ALOS-2 and Sentinel-1A data and the identification results of potential landslides, the reliability and applicability of ALOS-2 data in the identification of potential landslides in areas with dense vegetation cover and complex geological conditions were confirmed from the aspects of vegetation cover, topography, field investigation, and comparative analysis of typical landslides.
Assessing the Performance of WRF Model in Simulating Heavy Precipitation Events over East Africa Using Satellite-Based Precipitation Product
Authors: Nooni Isaac Kwesi , Tan Guirong , Hongming Yan , Saidou Chaibou Abdoul Aziz , Habtemicheal Birhanu Asmerom , Gnitou Gnim Tchalim , Lim Kam Sian Kenny T. C.
Published: April 2022

This study investigated the capability of the Weather Research and Forecasting (WRF) model to simulate seven different heavy precipitation (PRE) events that occurred across East Africa in the summer of 2020. The WRF model outputs were evaluated against high-resolution satellite-based observations, which were obtained from prior evaluations of several satellite observations with 30 stations’ data. The synoptic conditions accompanying the events were also investigated to determine the conditions that are conducive to heavy PRE. The verification of the WRF output was carried out using the area-related root mean square error (RMSE)-based fuzzy method. This method quantifies the similarity of PRE intensity distribution between forecast and observation at different spatial scales. The results showed that the WRF model reproduced the heavy PRE with PRE magnitudes ranging from 6 to >30 mm/day. The spatial pattern from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification-Climate Data Record (PERSIANN-CCS-CDR) was close to that of the WRF output. The area-related RMSE with respect to observation showed that the error in the model tended to reduce as the spatial scale increased for all the events. The WRF and high-resolution satellite data had an obvious advantage when validating the heavy PRE events in 2020. This study demonstrated that WRF may be used for forecasting heavy PRE events over East Africa when high resolutions and subsequent simulation setups are used.
Improving Forecast of Severe Oceanic Mesoscale Convective Systems Using FY-4A Lightning Data Assimilation with WRF-FDDA
Authors: Sun Hao , Wang Haoliang , Yang Jing , Zeng Yingting , Zhang Qilin , Liu Yubao , Gu Jiaying , Huang Shiye
Published: April 2022

The Fengyun-4A (FY-4A) geostationary satellite carries the Lightning Mapping Imager that measures total lightning rate of convective systems from space at high spatial and temporal resolutions. In this study, the performance of FY-4A lightning data assimilation (LDA) on the forecast of non-typhoon oceanic mesoscale convective systems (MCSs) is investigated by using an LDA method implemented in the Weather Research and Forecasting-Four Dimensional Data Assimilation (WRF-FDDA). With the LDA scheme, three-dimensional graupel mixing ratio fields retrieved from the FY-4A lightning data and the corresponding latent heating rates are assimilated into the Weather Research and Forecasting model via nudging terms. Two oceanic MCS cases over the South China Sea were selected to perform the study. The subjective evaluation results demonstrate that most of the oceanic convective cells missed by the control experiments are recovered in the analysis period by assimilating FY-4A lightning data, due to the promoted updrafts by latent-heat nudging, the more accurate and faster simulations of the cold pools, and the associated gust-fronts at the observed lightning locations. The cold pools and gust-fronts generated during the analysis period helped to maintain the development of the MCSs, and reduced the morphology and displacement errors of the simulations in the short-term forecast periods. The quantitative evaluation indicates that the most effective periods of the LDA for simulation enhancement were at the analysis time and the nowcasting (0–2 h forecast) periods.
The Dark Matter of Bilateral Preferential Margins: An Assessment of the Effect of US Tariffs
Authors: Cipollina Maria , Salvatici Luca
Published: April 2022

This article aimed to quantify the impact of United States (US) trade policies and assess how changes in tariff margins will affect imports to the US. To do that, we estimated trade elasticities by sector using a gravity structural model, computed US preference margins on a bilateral basis, and investigated alternative scenarios for properly measuring the effects of US trade agreements on international trade. Results showed that the removal of all preferences might lead to a negative net effect of $41,202 million (2% of predicted trade), indicating that the actual US structure of tariffs generates a trade diversion to less efficient exporters and destroys trade flows, even if the impact differs by sector.
Cybersecurity Skills among European High-School Students: A New Approach in the Design of Sustainable Educational Development in Cybersecurity
Authors: Jerman Blažič Borka , Jerman Blažič Andrej
Published: April 2022

Cybersecurity has increasingly become a headline feature in news media in recent years, generally prompted by spectacular security breaches in various information systems. The importance of cybersecurity awareness for the sustainable development of society is now recognized widely, but the problem of how to build an educational ecosystem which will include the most relevant target audiences that need to develop cybersecurity skills, is not yet solved. This paper elaborates the state of cybersecurity skills and knowledge in European high-school students by collecting data from the students, their teachers and parents by means of surveys and interviews in nine European countries. The analysis of the information collected has revealed the required topics from the area of cybersecurity that need to be introduced in high school educational programs and the most suitable delivery methods for educational content, such as videos and serious games. A selection of thirteen serious games related to cybersecurity was evaluated and then presented to a class of high-school students. The study of the collected data has shown that cybersecurity education at high school level requires innovative and interactive approaches that build the required skills for a more effective sustainable education and social development.
Investigating Learners’ Engagement and Chinese Writing Learning Outcomes with Different Designs of SVVR-Based Activities
Authors: Li Ming , Chen Yuting , Zhang Linjie , Wu Xuemei , Huang Changqin
Published: April 2022

The goal of this study is to explore the affordances of spherical video-based virtual reality (SVVR)-based learning activities by comparing the students’ learning engagement models and their writing learning outcomes in a double-loop SVVR-based (DL-SVVR) learning activity and a single-loop SVVR-based (SL-SVVR) learning activity, respectively. For this purpose, we conduct an empirical study involving 82 fourth-grade students. The statistical results show that the students in the DL-SVVR group had higher learning behavioral engagement and better writing learning outcomes than those in the SL-SVVR group. Furthermore, as for the interrelationship between the subscales of students’ learning engagement, we find that, for the students in SL-SVVR group, their behavioral engagement can be positively predicted by the emotional engagement, while in the DL-SVVR group, students’ behavioral engagement can be positively predicted by their social engagement. For both groups, their social engagement can positively predict the emotional engagement. Importantly, our empirical results also show that the double-loop learning approach can potentially promote students’ writing learning outcomes by shifting their social engagement and behavioral engagement. The qualitative analysis results indicate that peer interaction has a positive impact on improving students’ learning interest and writing outcomes.
To Adopt CCU Technology or Not? An Evolutionary Game between Local Governments and Coal-Fired Power Plants
Authors: Nie Shuai , Cai Guotian , Li Yixuan , Chen Yushu , Bai Ruxue , Gao Liping , Chen Xiaoyu
Published: April 2022

Carbon dioxide capture and utilization (CCU) technology is a significant means by which China can achieve its ambitious carbon neutrality goal. It is necessary to explore the behavioral strategies of relevant companies in adopting CCU technology. In this paper, an evolutionary game model is established in order to analyze the interaction process and evolution direction of local governments and coal-fired power plants. We develop a replicator dynamic system and analyze the stability of the system under different conditions. Based on numerical simulation, we analyze the impact of key parameters on the strategies of stakeholders. The simulation results show that the unit prices of hydrogen and carbon dioxide derivatives have the most significant impact: when the unit price of hydrogen decreases to 15.9 RMB/kg or the unit price of carbon dioxide derivatives increases to 3.4 RMB/kg, the evolutionary stabilization strategy of the system changes and power plants shift to adopt CCU technology. The results of this paper suggest that local governments should provide relevant support policies and incentives for CCU technology deployment, as well as focusing on the synergistic development of CCU technology and renewable energy hydrogen production technology.
An Analytic Model for Estimating the Economic and Environmental Impact of Food Cold Supply Chain
Authors: Bottani Eleonora , Casella Giorgia , Nobili Majcol , Tebaldi Letizia
Published: April 2022

Cold chain management has gained increasing interest among practitioners, researchers and academics; similarly, sustainability is also proving to be an increasingly critical topic in all supply chains and in cold chains in particular. In line with this, this study proposes a model to estimate the economic and environmental impacts in a food cold supply chain (FCSC). The model intended to estimate the total cost and CO2 emissions of a company operating in the cold supply chain, was carried out in Microsoft Excel™. Specifically, the model reproduces the main FCSC processes, i.e., Product collection, Backroom storage, Product delivery and Reverse logistics. For each process, we have exposed the implemented equations. Results show that the product delivery process is the most critical in both economic and environmental terms. Conversely, product collection and reverse logistics process contribute to the total cost and emission to a limited extent. The results obtained provide useful guidelines for supply chain managers to undertake operation decisions aimed at decreasing the economic and/or environmental impact of a FCSC.
Assessing Changes in the Value of Forest Ecosystem Services in Response to Climate Change in China
Authors: Xu Yuqing , Xiao Fengjin
Published: April 2022

Ecosystem services are the basis of human survival and development and play an irreplaceable role in maintaining the dynamic balance of the earth’s life support system and environment. This study evaluated the annual forest ecosystem service values (ESVs) and their spatial evolution characteristics from 2001 to 2020 in China and revealed the impact of climatic factors as well. The equivalent factor method was applied to calculate ESVs in combination with net primary productivity (NPP) calculated by the CASA model. The water conservation results based on the InVEST model and equivalent factor method were compared to test the reliability of the method. From 2001 to 2020, the annual forest ESVs ranged from RMB 9.17 trillion to 10.81 trillion, with an average of RMB 9.99 trillion in China. The forest ESVs increased from the northwest to the southeast regions of China with the lowest values of less than RMB 3 million per square kilometer and relatively high values of more than RMB 9 million per square kilometer. In the past 20 years, the forest ESVs have shown a significant increasing trend, especially in the Northeast Forest Region and Southeast Forest Region. The ESVs have decreased only in very few forest areas such as Cuona and Motuo counties on the southern edge of Tibet Province in Southwest China and Pingtung and Kaohsiung counties in southern Taiwan. The mean annual forest ESV was necessarily higher in the recent 10 years (2011–2020, RMB 10.43 trillion) than in the previous 10 years (2001–2010, RMB 9.55 trillion), while the spatial growth rate was usually less than 20%. The annual forest ESVs were significantly correlated with temperature, precipitation and evapotranspiration but not with sunshine hours and relative humidity across the 20 years. In most areas (>60%), the positive impact of various climatic factors was dominant, and the area positively affected by precipitation was the largest (76%). The mean annual forest water conservation from 2001 to 2020 was RMB 1.46 trillion based on the InVEST model and was RMB 1.77 trillion based on the equivalent factor method. Overall, the results obtained by the two methods are roughly equal and mostly spatially matched. This study has some guiding significance for utilizing resources rationally, strengthening ecological environment protection and improving adaptability to climate change.
Analysis of a Hybrid Wind/Photovoltaic Energy System Controlled by Brain Emotional Learning-Based Intelligent Controller
Authors: Albalawi Hani , El-Shimy Mohamed E. , AbdelMeguid Hosam , Kassem Ahmed M. , Zaid Sherif A.
Published: April 2022

Recently, hybrid wind/PV microgrids have gained great attention all over the world. It has the merits of being environmentally friendly, reliable, sustainable, and efficient compared to its counterparts. Though there has been great development in this issue, the control and energy management of these systems still face challenges. The source of those challenges is the intermittent nature of both wind and PV energy. On the other hand, a new intelligent control technique called Brain Emotional Learning-Based Intelligent Controller (BELBIC) has garnered more interest. This paper proposes the control and energy management of hybrid wind/PV microgrids using a BELBIC controller. To design the system, simple power and energy analyses were proposed. The proposed microgrid was modeled and simulated using MATLAB. The responses of the energy system were tested under two different types of disturbances, namely step and ramp disturbances. These disturbances are applied to the wind speed, the irradiation level of the PV, and the load power. The results indicate that the AC load voltage and frequency are steady with negligible transients against the previous disturbance. In addition, the performance is better than that of the classical PI controller. Also, energy management acts perfectly to compensate for the intermittence and disturbances of the wind and PV energies. On the other hand, the system robustness against model parameters uncertainties in the microgrid parameters are studied.
Evaluation of the Interventions to Built Heritage: Analysis of Selected Façades of Kaunas by Space Syntax and Sociological Methods
Authors: Zaleckis Kęstutis , Doğan Huriye Armağan , Arce Natanael Lopez
Published: April 2022

This paper is an attempt to analyse the correlation between the perception of people and their evaluation regarding contemporary interventions and changes on the façades of cultural heritage buildings, which might affect cultural sustainability. The paper uses two different experimental methods for the analysis of the building façades from various eras in the city centre of Kaunas, which experienced interventions that affected the appearance of the structures. The first experiment performed is a sociological survey, and the second one is a façade analysis conducted by the space syntax method. The paper follows the theory of Nikos Salingaros for measuring the properties of the size distribution on the façades and implements Bill Hillier’s methodology for symmetry index analysis. The research demonstrates some significant correlations between the results of Space Syntax modelling and the sociological survey answers, thus demonstrating the possibility of modelling and predicting changes in the perception of architectural transformations of the façades with potential usability in the monitoring of the transformation of cultural heritage objects, preservation of the cultural identity of a cityscape, etc.
Seasonal Variations and Influencing Factors of Gross Nitrification Rate in Desert Steppe Soil
Authors: Qiu Xiao , Hou Jia , Guo Na , Wang Zhanyi , Wang Chengjie
Published: April 2022

Nitrification plays an important role in nitrogen (N) turnover and N cycling. To date, there have been many studies on the net N turnover in grassland. However, few studies have specifically focused on the gross N turnover, which is mainly due to methodological limitations. Here, we set up an enclosed plot in a desert steppe and determined the gross nitrification (GN) rate of the soil by using the barometric process separation method. We found the seasonal dynamics of the GN in the desert steppe soil, such that the GN in the summer (117.65 ± 24.86 μg N kg−1 h−1) was significantly greater than in the spring and autumn (65.17 ± 7.33 μg N kg−1 h−1), and it peaked in July (213.75 ± 44.66 μg N kg−1 h−1). Additionally, the GN was lowest in the spring, with a means of 50.52 ± 3.95 μg N kg−1 h−1. The seasonal variation in the GN was different than the seasonal variation in the net nitrification rate, and the GN was generally much higher than the net nitrification rate. We further demonstrated that the soil moisture, temperature, bulk density and NH4+-N were the main factors that influenced the seasonal variations in the GN, and that the soil moisture had the greatest impact on the GN among all the factors measured.
Workplace Loneliness and the Need to Belong in the Era of COVID-19
Authors: Du Shuyun , Ma Yinan , Lee Jeoung Yul
Published: April 2022

On the basis of Social Exchange Theory (SET), Knowledge Stickiness Theory (KST), and the need-to-belong hypotheses, we empirically studied the causes and consequences of workplace loneliness in interpersonal communication and explored the moderating effect of the need to belong. We distributed a survey and collected 639 valid responses in mainland China in both paper and electronic form during the period of February to October 2020, when the COVID-19 crisis was severe. Mplus was used to create a latent structural equation model with a moderating mediating model. Collaborative and competitive intrateam climates affect employees’ workplace loneliness and knowledge hoarding from different aspects. We also verified a moderated mediation model. Thus, this study examines the mediating effect of workplace loneliness and introduces the need to belong as the moderating variable; reveals the formation mechanism of workplace loneliness in collaborative and competitive intrateam climates; and deepens the research on the effective regulation of workplace loneliness. As the COVID-19 pandemic remains ongoing, we have verified changes to the mediating effect of workplace loneliness, driven by the motivation of the need to belong, and clearly evaluated a moderated mediating effect path, which contributes to the theory of belonging.
Collaboration in Value Constellations for Sustainable Production: The Perspective of Small Technology Solution Providers
Authors: Rahnama Hossein , Johansen Kerstin , Larsson Lisa , Rönnbäck Anna Öhrwall
Published: April 2022

The rapid ongoing digital transformation creates new opportunities to generate value but also challenges companies in the manufacturing industry to adapt to the recent changes. Moreover, committing to sustainability is essential to maintain competitive advantages, build a more resilient company, and manage increasing societal demands and regulations. Referred to as a “twin transition”, the digital transformation can positively impact firms’ commitments to environmental sustainability. This paper explores challenges that small technology solution providers face on their path toward developing sustainable production solutions for their manufacturing customers. An empirical study was conducted in an industrial cluster of small and medium-sized companies (SMEs) providing innovative, tailor-made production technology solutions to manufacturing companies. As a result, a collaborative process model was suggested for such SMEs to overcome internal and external barriers to obtaining sustainability, thus better supporting the manufacturing companies, i.e., their customers, to strive towards more sustainable production.
Determinants of Economic Growth across the European Union: A Panel Data Analysis on Small and Medium Enterprises
Authors: Batrancea Larissa M.
Published: April 2022

Across the European Union, small and medium enterprises (SMEs) are major contributors to the increase of the regional gross domestic product. The present study investigates the relationship between economic growth, imports and exports regarding the activity of small and medium enterprises within the European Union (EU-28). A panel generalized method of moments (GMM) analysis and a panel two-stage least squares (2SLS) analysis were carried out for the period 2005–2020. Empirical results indicated that online imports and exports together with extra-EU imports and exports had a significant impact on economic growth, proxied by value added, venture capital investments and turnover from e-commerce. In the light of these results, regional and national authorities are called to support business endeavors of small and medium enterprises due to their relevance on the market and contribution to the financing of national budgets.
A Study on the Flame-Retardant Performance of Recycled Paper Building Materials Manufactured by 3D Printer
Authors: Hwang Jeo , Park Dongin , Kim Subin , Rie Dongho
Published: April 2022

The increase in non-face-to-face lifestyles due to COVID-19 worldwide have shown an increase in delivery services. The number of parcels in 2020 was 3.373 billion, an increase of 20.9% from 2.788 billion in 2019. This phenomenon increased delivery box waste. Against this background, this study attempted to develop building materials from the recycling of delivery boxes. In this study, the self-developed WC (wet cellulose) 3D printer confirmed the standardization and uniform performance of the sample by filling the material supply cylinder with cellulose filaments and spraying the composite material through a 10 mm nozzle. The cellulose filament for a WC 3D printer is based on cellulose extracted from wastepaper, and a cellulose filament composite material is used by mixing additives. After manufacturing a specimen using the WC 3D printer, a reliability test for the flame-retardant performance of the material was conducted according to the ISO 11925-2 test method. As a result of the experiment, flame-retardant performance was confirmed at a 40 wt% or greater ceramic binder content. In addition, the WC 3D printer achieved accurate test results by producing specimens with uniform physical properties. In addition, we confirmed that 3D-printed WC can be used to develop customized building materials that can prevent fire spread.
Sustainable Supplier’s Equilibrium Discount Strategy under Random Demand
Authors: Li Yingxiao , Zhou Jianheng
Published: April 2022

This paper examines a sustainable supplier’s price discount strategy in a competitive environment as it considers building a two-level supply chain system consisting of two suppliers and a single retailer under the condition of uncertain demand, and investigates the impact of the suppliers’ price discount strategy on the retailer’s expected profits. We find that the sustainable supplier’s expected profit increases as the price discount increases. When only the sustainable supplier offers a discount, the retailer’s purchasing cost will increase with the degree of the discount; when both suppliers provide a discount, the sustainable supplier’s expected profit decreases as the price discount increases, while the retailer’s purchasing cost will decrease.
Potential Hydrogen Market: Value-Added Services Increase Economic Efficiency for Hydrogen Energy Suppliers
Authors: Zhao Wenhui , Ma Jibin , Wang Zhanyang , Li Youting , Zhang Weishi
Published: April 2022

Hydrogen energy is a clean, zero-carbon, long-term storage, flexible and efficient secondary energy. Accelerating the development of the hydrogen energy industry is a strategic choice to cope with global climate change, achieve the goal of carbon neutrality, and realize high-quality economic and social development. This study aimed to analyze the economic impact of introducing value-added services to the hydrogen energy market on hydrogen energy suppliers. Considering the network effect of value-added services, this study used a two-stage game model to quantitatively analyze the revenue of hydrogen energy suppliers under different scenarios and provided the optimal decision. The results revealed that (1) the revenue of a hydrogen energy supplier increases only if the intrinsic value of value-added services exceeds a certain threshold; (2) the revenue of hydrogen energy suppliers is influenced by a combination of four key factors: the intrinsic value of value-added services, network effects, user scale, and the sales strategies of rivals; (3) the model developed in this paper can provide optimal decisions for hydrogen energy suppliers to improve their economic efficiency and bring more economic investment to hydrogen energy market in the future.
The Future Climate under Different CO2 Emission Scenarios Significantly Influences the Potential Distribution of Achnatherum inebrians in China
Authors: Jiang Jia-Min , Jin Lei , Huang Lei , Wang Wen-Ting
Published: April 2022

The threat posed by poisonous weeds to grassland ecosystems may be exacerbated by climate change mainly driven by carbon dioxide (CO2) emissions. Achnatherum inebrians is a common and poisonous grassland weed that is seriously endangering the sustainable development of prairie animal husbandry in Western China. Understanding the influence of future climate change under different CO2 emission scenarios on the potential distributions of A. inebrians is critical for planning agricultural strategies to manage the continued invasion. An ecological niche model (ENM) was developed using Maxent to predict the potential distribution of A. inebrians under three different CO2 emission scenarios. Occurrence records of A. inebrians were selected utilizing the nearest neighbor method. Six environmental variables, which were identified through principal component analysis, correlation analysis and their contribution rates, were used to perform the ENM. At the same time, considering the uncertainties of predicting future climates, four global circulation models were used for the Maxent projections with average results calculated. Our results demonstrate differential influences of various CO2 emission scenarios on the potential distributions of A. inebrians. Before 2050, high CO2 emission scenarios resulted in a wider potential distribution of A. inebrians, when compared to low CO2 emission scenarios. However, after 2050, the low CO2 emission scenarios were more conducive to an expanded potential distribution. In addition, after 2050, high CO2 emission scenarios maintain the geographical distribution centroids of A. inebrians in lower latitudes, while low CO2 emission scenarios result in distribution centroids rising to higher latitudes. Further, low CO2 emission scenarios resulted in the average potential distribution elevation dropping lower than in high CO2 emission scenarios.
Functional Bakery Snacks for the Post-COVID-19 Market, Fortified with Omega-3 Fatty Acids
Authors: Karantonis Haralabos C. , Nasopoulou Constantina , Skalkos Dimitris
Published: April 2022

Flaxseed is a natural ingredient with health benefits because of its rich contents of omega-3 fatty acids and fiber. In this study, whole-meal sliced bread, chocolate cookies, and breadsticks, which were enriched with flaxseed (Linum usitatissimu) were produced as a natural enrichment source in order to provide functional baked goods. The three innovative products were tested as sources of omega-3 fatty acids in terms of α-linolenic acid according to EU 1924/2006 as well as for their in vitro antithrombotic/anti-inflammatory effect. The results showed that omega-3 fatty acids had high concentrations (>0.6 g per 100 g of product) in all products even after the heating treatment with constant stability during the time of consumption. All the enriched products exerted higher, but in different grade, in vitro antithrombotic/anti-inflammatory activity compared to the conventional products. The products were evaluated positively by a panel of potential consumers without significant differences compared to conventional corresponding products. Enriched bakery products with omega-3 fatty acids may represent a novel opportunity for the development of functional foods that can be locally consumed, thereby contributing to public health prevention measures that the post-COVID-19 era demands.
Effects of Functional Diversity on Soil Respiration in an Arid Desert Area
Authors: Liu Feiyi , Wang Jinlong , Shu Yulin , Lv Guanghui
Published: April 2022

To compare the relative importance of the biomass ratio hypothesis and the niche complementarity hypothesis in explaining changes in soil respiration (Rs), and to explore whether the relationship between biodiversity and Rs was affected by both biotic and abiotic factors, dynamic plant community monitoring was conducted in the Ebinur Lake Wetland Nature Reserve. By calculating the functional diversity (FD), community-weighted mean functional traits (CWM), and soil factors, the correlation between FD and Rs was compared using a linear regression model and a structural equation model. The results showed that (1) the CWM traits could better explain the changes of Rs than the FD, indicating that the biomass ratio hypothesis was more suitable for explaining changes in Rs in arid desert areas; and (2) the correlation between biodiversity and Rs was affected by the interaction between biological factors and environmental factors. Soil water content and species richness also affected Rs. Research on the relationship between biodiversity and Rs should examine both biotic and abiotic factors and clarify and explore various factors affecting Rs, which is of great significance to evaluate the community dynamics and variation characteristics of Rs. The study of various factors affecting Rs in this region is helpful to elucidate the process of the soil carbon cycle in arid desert areas.
Our New Artificial Intelligence Infrastructure: Becoming Locked into an Unsustainable Future
Authors: Robbins Scott , van Wynsberghe Aimee
Published: April 2022

Artificial intelligence (AI) is becoming increasingly important for the infrastructures that support many of society’s functions. Transportation, security, energy, education, the workplace, the government have all incorporated AI into their infrastructures for enhancement and/or protection. In this paper, we argue that not only is AI seen as a tool for augmenting existing infrastructures, but AI itself is becoming an infrastructure that many services of today and tomorrow will depend upon. Considering the vast environmental consequences associated with the development and use of AI, of which the world is only starting to learn, the necessity of addressing AI alongside the concept of infrastructure points toward the phenomenon of carbon lock-in. Carbon lock-in refers to society’s constrained ability to reduce carbon emissions technologically, economically, politically, and socially. These constraints are due to the inherent inertia created by entrenched technological, institutional, and behavioral norms. That is, the drive for AI adoption in virtually every sector of society will create dependencies and interdependencies from which it will be hard to escape. The crux of this paper boils down to this: in conceptualizing AI as infrastructure we can recognize the risk of lock-in, not just carbon lock-in but lock-in as it relates to all the physical needs to achieve the infrastructure of AI. This does not exclude the possibility of solutions arising with the rise of these technologies; however, given these points, it is of the utmost importance that we ask inconvenient questions regarding these environmental costs before becoming locked into this new AI infrastructure.
Impact of Artificial Intelligence News Source Credibility Identification System on Effectiveness of Media Literacy Education
Authors: Chiang Tosti H. C. , Liao Chih-Shan , Wang Wei-Ching
Published: April 2022

During presidential elections and showbusiness or social news events, society has begun to address the risk of fake news. The Sustainable Development Goals 4 for Global Education Agenda aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” by 2030. As a result, various nations have deemed media literacy education a required competence in order for audiences to maintain a discerning attitude and to verify messages rather than automatically believing them. This study developed a highly efficient message discrimination method using new technology using artificial intelligence and big data information processing containing general news and content farm message data on approximately 938,000 articles. Deep neural network technology was used to create a news source credibility identification system. Media literacy was the core of the experimental course design. Two groups of participants used different methods to perform message discrimination. The results revealed that the system significantly expanded the participants’ knowledge of media literacy. The system positively affected the participants’ attitude, confidence, and motivation towards media literacy learning. This research provides a method of identifying fake news in order to ensure that audiences are not affected by fake messages, thereby helping to maintain a democratic society.
Challenges and Adaptive Measures for U.S. Municipal Solid Waste Management Systems during the COVID-19 Pandemic
Authors: Pinto Ana Daniela , Jalloul Hiba , Nickdoost Navid , Sanusi Fehintola , Choi Juyeong , Abichou Tarek
Published: April 2022

The coronavirus pandemic has resulted in major disruptions in the way municipal solid waste management systems (MSWMSs) operate due to substantial distortions in waste generation trends, along with a variety of significant operational and managerial challenges. As critical infrastructure, MSWMSs have endeavored to adapt in response to such unprecedented stresses in order to maintain their operations during the pandemic. The challenges and their relevant adaptive measures, however, have varied with the progression of the pandemic across different MSWMSs. Currently, there is a limited understanding of such time-bound and system-specific phenomena, which impedes timely and effective adaptation. This study aims to fill this knowledge gap by performing a detailed and documented investigation of the longitudinal impact of the coronavirus pandemic on different MSWMSs across the United States, along with its evolution over time, using collected qualitative and quantitative data (i.e., monthly interviews with waste management personnel, online news media, and waste tonnages). This study also develops a relational database system to facilitate the systematic recording and monitoring of the pandemic’s impact on MSWMSs, as well as guide the implementation of different adaptation strategies based on distinct systems’ characteristics. Findings of this study will help solid waste decision-makers better understand the current pandemic, along with serving as a knowledge base for future pandemic scenarios towards more resilient MSWMSs.
The Evaluation of Active Learning Classrooms: Impact of Spatial Factors on Students’ Learning Experience and Learning Engagement
Authors: Peng Lei , Deng Yuan , Jin Shitao
Published: April 2022

Previous studies have investigated the spatial attributes of Active Learning Classrooms (ALCs) and their impact on students’ learning experiences and learning engagement independently; however, a holistic investigation of the relationship between these attributes and students’ learning engagement has not been conducted. This study explored how the spatial attributes of ALCs affect students’ learning experiences and learning engagement. An empirical questionnaire was administered to freshmen taking English classes in four different types of ALCs at one university, and 224 valid questionnaires were analyzed. This study provides design insight for future learning environments in ALCs by linking two Likert scales: one rating spatial attributes in ALCs that influence learning experiences, and the other rating students’ learning engagement in ALCs. The results revealed that the spatial attributes of ALCs significantly affected the learning experience, specifically instructional interaction, furniture perception, learning support, and physical environment. Among them, instructional interactions and physical environment are the most critical in promoting student learning engagement. The survey findings can help architects design more flexible and sustainable learning environments in the future, supporting university students in developing active and collaborative learning skills, as well as providing better references and beneficial insights for future education for sustainable development.
Revising Technology Adoption Factors for IoT-Based Smart Campuses: A Systematic Review
Authors: Sneesl Radhwan , Jusoh Yusmadi Yah , Jabar Marzanah A. , Abdullah Salfarina
Published: April 2022

Smart education and the sustainable development of smart campuses have drawn significant research attention. This is enabled by intelligent devices that are widely attracting massive applicability in personal and big business contexts and can increase efficiency and convenience. This paper aims to present a solution to address the lack of a proper adoption model for smart campus initiatives. The evaluation and synthesis of the literature were conducted by following the systematic literature review (SLR) procedure. The study’s findings revealed the taxonomy and IoT technologies leading to the wide adoption of IoT-based smart campuses. The technology adoption models and their corresponding variables help the authors identify and classify a suitable adoption framework for smart campuses. The limitations and challenges of adoption theories as they pertain to smart campuses are discussed. Finally, the study adapts perceived scalability, perceived replicability, perceived reliability, perceived privacy and security, perceived trust, the cost of deployment, usefulness, enjoyment, and technicality as adoption factors of sustainable smart campuses. This study offers practical and theoretical implications regarding the adoption and propagation of emerging smart campuses.
Population Prediction of Chinese Prefecture-Level Cities Based on Multiple Models
Authors: Chen Lixuan , Mu Tianyu , Li Xiuting , Dong Jichang
Published: April 2022

In recent years, the population growth rate has been gradually declining in China. As the population problem becomes increasingly significant, the accurate prediction of population development trends has become a top priority, used to facilitate national scientific planning and effective decision making. Based on historical data spanning a period of 20 years (1999–2018), this article presents predictions of the populations of 210 prefecture-level cities using the Malthusian model, Unary linear regression model, Logistic model, and Gray prediction model. Furthermore, because the gray prediction model exhibited the highest degree of accuracy in formulating predictions, this study uses the model to predict and analyze future population development trends. The results reveal that the population gap between cities is gradually widening, and the total urban population shows a pattern of rising in middle-tier cities (second-tier cities and third-tier cities) and declining in high-tier cities (first-tier cities and new first-tier cities) and low-tier cities (fourth-tier cities and fifth-tier cities). From the viewpoint of geographical distribution, the population growth rate is basically balanced between the northern part and the southern part of China. In addition, the population growth of the high-tier cities is gradually slowing while the low-tier cities are experiencing a negative growth of population, but middle-tier cities are experiencing skyrocketing population growth. From the viewpoint of regional development, although the development of regional integration has been strengthened over the years, the radiative driving effect of large urban agglomerations and metropolitan areas is relatively limited.
Child-Friendly Environments—What, How and by Whom?
Authors: Jansson Märit , Herbert Emma , Zalar Alva , Johansson Maria
Published: April 2022

The socio-physical qualities of built environments are, in several ways, of imperative importance for children growing up. The Child-Friendly Cities initiative by UNICEF, an implementation of the UN Convention on the Rights of the Child, has made local governments strive toward child-friendliness. The participation of children and young people is often the focus of such projects, with a potential for a far broader scope. Besides participation processes, what important socio-physical qualities make environments child-friendly, and how can they be developed? This paper presents a structured literature review of the concept of child-friendly environments, in order to address the full socio-physical spectrum. The results focus on concrete factors that have been filtered through child-friendliness and the associated frameworks, showing an inherent dependence between the social context and the physical environment. The shaping of child-friendliness hinges on the realization of environments that are safe, fair, and with accessible and variable green and open spaces. A multi-stakeholder endeavor including, e.g., planners, designers, and managers requires clearly outlined priorities. This study lays the groundwork for further exploration of how the concept of child-friendly environments can lead to positive changes, also as part of the overall strive toward sustainable development.
Bio-Based Plastics Production, Impact and End of Life: A Literature Review and Content Analysis
Authors: Abrha Halayit , Cabrera Jonnathan , Dai Yexin , Irfan Muhammad , Toma Abrham , Jiao Shipu , Liu Xianhua
Published: April 2022

The accumulation of plastic wastes is one of the most widely spread problems affecting the environment. The reality that plastics can be made from renewable resources and degrade naturally has prompted academics to think outside the box to develop “better for the environment” items. In this paper, a bibliometric analysis of the scholarly publications related to bio-based plastics within the last 20 years is presented. Annual progression, geographic and research area distribution, and keyword co-occurrence were all examined. Six distinct clusters emerged from keyword analysis, which were further categorized into three directions: production to marketing; impact on the environment, economy, and society; and end-of-life (EoL) options. The major focus was on how to counter the weaknesses and challenges of bio-based plastics and take opportunities using the inherent advantages of bio-based plastics. Comprehensive studies regarding the impact of bio-based plastics on the environment, economy and social sustainability are still deficient. Although there are many promising innovations in this area, most of them are at the research stage. The benefits of bio-based plastics and better EoL options can be enjoyed only after increased production.