bluuebunny/crossref_metadata_2025 huggingface dataset:
Extracting Remotely Sensed Water Quality Parameters from Shallow Intertidal Estuaries
Authors: Shao Zhanchao , Bryan Karin R. , Lehmann Moritz K. , Pilditch Conrad A.
Published: December 2022

Sentinel-2 imagery is potentially ideal for providing a rapid assessment of the ecological condition of estuarine water due to its high temporal and spatial resolution and coverage. However, for optically shallow waters, the problem of isolating the effect of seabed reflectance from the influence of water properties makes it difficult to use the observed surface reflectance to monitor water quality. In this study, we adopt a methodology based on Lyzenga’s model to estimate water quality properties such as the dominant wavelength and diffuse attenuation coefficient (Kd) of shallow estuarine waters. Lyzenga models the observed reflectance (R) using four parameters: total water depth (z), sea-bed reflectance (Rb), water reflectance (Rw) and Kd. If Rb is known a priori and multiple observations of R are available from different total water depths, we show that Lyzenga’s model can be used to estimate the values of the remaining two parameters, Kd and Rw. Observations of R from different water depths can either be taken from the same image at different proximal locations in the estuary (“spatial method”) or from the same pixel observed at different tidal stages (“temporal method”), both assuming homogeneous seabed and water reflectance properties. Tests in our case study estuary show that Kd and Rw can be estimated at water depths less than 6.4 m. We also show that the proximity restriction for the reflectance correction with the temporal method limits outcomes to monthly or seasonal resolution, and the correction with the spatial method performs best at a spatial resolution of 60 m. The Kd extracted from the blue band correlates well with the observed Kd for photosynthetically active radiation (PAR) (r2 = 0.66) (although the relationship is likely to be estuary-specific). The methodology provides a foundation for future work assessing rates of primary production in shallow estuaries on large scales.
Deep Unfolded Gridless DOA Estimation Networks Based on Atomic Norm Minimization
Authors: Zhu Hangui , Feng Weike , Feng Cunqian , Ma Teng , Zou Bo
Published: December 2022

Deep unfolded networks have recently been regarded as an essential way to direction of arrival (DOA) estimation due to the fast convergence speed and high interpretability. However, few consider gridless DOA estimation. This paper proposes two deep unfolded gridless DOA estimation networks to resolve the above problem. We first consider the atomic norm-based 1D and decoupled atomic norm-based 2D gridless DOA models solved by the alternating iterative minimization of variables, respectively. Then, the corresponding deep networks are trained offline after constructing the corresponding complete training datasets. At last, the trained networks are applied to realize the 1D DOA and 2D estimation, respectively. Simulation results reveal that the proposed networks can secure higher 1D and 2D DOA estimation performances while maintaining a lower computational expenditure than typical methods.
Combining Hyperspectral, LiDAR, and Forestry Data to Characterize Riparian Forests along Age and Hydrological Gradients
Authors: Godfroy Julien , Lejot Jérôme , Demarchi Luca , Bizzi Simone , Michel Kristell , Piégay Hervé
Published: December 2022

Riparian forests are complex ecosystems shaped by their connectivity to a river system, which produces a mosaic of ages and species. Because of increasing anthropic pressure from factors such as damming or climate change, they are often endangered and suffer from a drop in groundwater accessibility and increased water stress. By combining hyperspectral, LiDAR, and forestry datasets along a 20 km corridor of the Ain River, this paper assesses the ability of remote sensing to characterize and monitor such environments. These datasets are used to investigate changes in site conditions and forest characteristics, such as height and canopy water content, along a gradient of ecosystem ages and for reaches under distinct geomorphic conditions (shifting, sediment-starved, incised). The data show that, over time, forest patches aggrade, and the forest grows and becomes more post-pioneer. However, forest patches that are located in the incised reach aggrade more and appear to be less developed in height, more stressed, and feature species compositions reflecting dryer conditions, in comparison with better-connected patches of the same age. Random forest analysis was applied to predict the indicators of forest connectivity with remotely sensed LIDAR and hyperspectral data, in order to identify the spatial trends at the reach scale and compare them with the geomorphic segmentation of the river. The random forest classifications achieved an accuracy between 80% and 90% and resulted in spatial trends that highlighted the differences in hydrological connectivity between differing geomorphic conditions. Overall, remote sensing appears to be a good tool for characterizing the impact of channel incisions and adjustments on riparian forest conditions by identifying the locations of dryer forest patches. In addition, good accuracy was achieved when attempting to classify these forest patches, even when using hyperspectral data alone, which suggests that satellite data could become a powerful tool for monitoring the health of riparian forests, in the context of increasing anthropic pressures.
Applying Variable Selection Methods and Preprocessing Techniques to Hyperspectral Reflectance Data to Estimate Tea Cultivar Chlorophyll Content
Authors: Sonobe Rei , Hirono Yuhei
Published: December 2022

Tea is second only to water as the world’s most popular drink and it is consumed in various forms, such as black and green teas. A range of cultivars has therefore been developed in response to customer preferences. In Japan, farmers may grow several cultivars to produce different types of tea. Leaf chlorophyll content is affected by disease, nutrition, and environmental factors. It also affects the color of the dried tea leaves: a higher chlorophyll content improves their appearance. The ability to quantify chlorophyll content would therefore facilitate improved tea tree management. Here, we measured the hyperspectral reflectance of 38 cultivars using a compact spectrometer. We also compared various combinations of preprocessing techniques and 14 variable selection methods. According to the ratio of performance to deviation (RPD), detrending was effective at reducing the influence of additive interference of scattered light from particles and then regression coefficients was the best variable selection method for estimating the chlorophyll content of tea leaves, achieving an RPD of 2.60 and a root mean square error of 3.21 μg cm−2.
Soil Erosion Satellite-Based Estimation in Cropland for Soil Conservation
Authors: Gallo Bruna Cristina , Magalhães Paulo Sérgio Graziano , Demattê José A. M. , Cervi Walter Rossi , Carvalho João Luís Nunes , Barbosa Leandro Carneiro , Bellinaso Henrique , Mello Danilo César de , Veloso Gustavo Vieira , Alves Marcelo Rodrigo , Fernandes-Filho Elpídio Inácio , Francelino Márcio Rocha , Schaefer Carlos Ernesto Gonçalves Reynaud
Published: December 2022

Intensive cropland expansion for an increasing population has driven soil degradation worldwide. Modeling how agroecosystems respond to variations in soil attributes, relief and crop management dynamics can guide soil conservation. This research presents a new approach to evaluate soil loss by water erosion in cropland using the RUSLE model and Synthetic Soil Image (spectroscopy technique), which uses time series remotely sensed environmental, agricultural and anthropic variables, in the southeast region of São Paulo State, Brazil. The availability of the open-access satellite images of Tropical Rainfall Measuring Mission (TRMM) and Landsat satellite images provided ten years of rainfall data and 35 years of exposed soil surface. The bare soil surface and agricultural land use were extracted, and the multi-temporal rainfall erosivity was assessed. We predict soil maps’ attributes (texture and organic matter) through innovative soil spectroscopy techniques to assess the soil erodibility and soil loss tolerance. The erosivity, erodibility, and topography obtained by the Earth observations were adopted to estimate soil erosion in four scenarios of sugarcane (Saccharum spp.) residue coverage (0%, 50%, 75%, and 100%) in five years of the sugarcane cycle: the first year of sugarcane harvest and four subsequent harvesting years from 2013 to 2017. Soil loss tolerance means 4.3 Mg ha−1 exceeds the minimum rate in 40% of the region, resulting in a total soil loss of ~6 million Mg yr−1 under total coverage management (7 Mg ha−1). Our findings suggest that sugarcane straw production has not been sufficient to protect the soil loss against water erosion. Thus, straw removal is unfeasible unless alternative conservation practices are adopted, such as minimum soil tillage, contour lines, terracing and other techniques that favor increases in organic matter content and soil flocculating cations. This research also identifies a spatiotemporal erosion-prone area that requests an immediately sustainable land development guide to restore and rehabilitate the vulnerable ecosystem service. The high-resolution spatially distribution method provided can identify soil degradation-prone areas and the cropland expansion frequency. This information may guide farms and the policymakers for a better request of conservation practices according to site-specific management variation.
Assessment of Economic Recovery in Hebei Province, China, under the COVID-19 Pandemic Using Nighttime Light Data
Authors: Li Feng , Liu Jun , Zhang Meidong , Liao Shunbao , Hu Wenjie
Published: December 2022

The COVID-19 pandemic has presented unprecedented disruptions to human society worldwide since late 2019, and lockdown policies in response to the pandemic have directly and drastically decreased human socioeconomic activities. To quantify and assess the extent of the pandemic’s impact on the economy of Hebei Province, China, nighttime light (NTL) data, vegetation information, and provincial quarterly gross domestic product (GDP) data were jointly utilized to estimate the quarterly GDP for prefecture-level cities and county-level cities. Next, an autoregressive integrated moving average model (ARIMA) model was applied to predict the quarterly GDP for 2020 and 2021. Finally, economic recovery intensity (ERI) was used to assess the extent of economic recovery in Hebei Province during the pandemic. The results show that, at the provincial level, the economy of Hebei Province had not yet recovered; at the prefectural and county levels, three prefectures and forty counties were still struggling to restore their economies by the end of 2021, even though these economies, as a whole, were gradually recovering. In addition, the number of new infected cases correlated positively with the urban NTL during the pandemic period, but not during the post-pandemic period. The study results are informative for local government’s strategies and policies for allocating financial resources for urban economic recovery in the short- and long-term.
Wellbeing and (Mental) Health: A Quantitative Exploration of Portuguese Young Adults’ Uses of M-Apps from a Gender Perspective
Authors: Antunes Eduardo , Alcaire Rita , Amaral Inês
Published: December 2022

Acknowledging the importance of technology in the mental health and wellbeing of individuals during the COVID-19 pandemic, this paper aims to analyse the uses of mobile health applications by young Portuguese adults focusing on the following research question: How do the uses of m-apps by young adults interact with health and wellbeing from a gender perspective? An online survey was conducted to a representative sample of young Portuguese adults (18–30 years), under the objectives of the MyGender project that studies the interconnections of young adults with m-apps, with their technicity and imaginaries. The approach followed in this paper is quantitative-extensive. Results reveal low usage of overall health and wellbeing apps, particularly among single respondents who do not have children. Health and self-tracking apps are among the 10 most frequently used apps. Only 6.20% of the sample considers mental health apps (mHapps) as one of the three most important types of apps. Having children is a factor for a bigger interconnectedness of the respondents with overall health and wellbeing apps and the general quality of care.
Students and Staff in Lockdown: Mental and Social Health in the Austrian Tertiary Education Sector
Authors: Noehammer Elisabeth
Published: December 2022

The SARS-CoV-2 pandemic led to high demands on the educational sector. For tertiary education, investigations mostly focused on the effects of digital teaching. However, little is known regarding health effects. Moreover, the emphasis was mainly on students, not university staff members. An international online questionnaire consisting of quantitative and qualitative items (from the LockedDown project) was translated into German and used in Austria from June to November 2020. This study reports on social and psychological health plus the perceived benefits of the pandemic. A total of 1175 students and 716 staff members participated. While staff members reported higher stress levels at the beginning of the pandemic, they were more pronounced for students from Week 5 onwards (Chi2 < 0.001). Quality of Life (QoL) decreased more in the student population, and depression/anxiety was higher and rose compared to staff. Moreover, students reported fewer benefits of the pandemic. Students perceived the burden of the pandemic later than staff members who needed to adapt their work processes immediately. Mental health interventions in a pandemic seem to be needed at different points in time depending on the target group.
Relations between Parenting Style and Parenting Practices and Children’s School Achievement
Authors: Tsela Dimitra , Tsela Rosie Drosou , López Ignacio González
Published: December 2022

This study examines the relationship between parenting patterns and children’s school achievements in Greek society. Parenting practices and parenting style are two child-rearing dynamics which were selected to assess children’s school achievements in this study. A total of 101 participants who have at least one child attaining elementary school and who reside in Greece answered an online questionnaire. In line with previous findings, the aim of this study is to examine associations between parenting and primary school students’ achievements in Greece. The initial assumption was that both parenting practices and parenting style are associated with academic achievement. Thus, the primary hypotheses under examination in this study are (A) that authoritarian parenting pattern is negatively associated with school achievement; (B) that authoritative parenting style is positively associated with school achievement; and (C) that parental involvement affects children and their school performance. The results show a positive relation between authoritative parenting styles and children’s school achievement, although the authoritarian style was associated with lower levels of school achievement. Additionally, the results indicate that the authoritarian style combined with involvement practices is a significant predictor of grades. The more authoritative means that parents use to socialize with their children, the more likely they are to achieve their parenting goals. Nevertheless, it is of critical importance for parents to focus on the learning process and not on the outcome.
Corrosion Compatibility of Stainless Steels and Nickel in Pyrolysis Biomass-Derived Oil at Elevated Storage Temperatures
Authors: Jun Jiheon , Su Yi-Feng , Keiser James R. , Wade John E. , Kass Michael D. , Ferrell Jack R. , Christensen Earl , Olarte Mariefel V. , Sulejmanovic Dino
Published: December 2022

Corrosion compatibility of stainless steels and nickel (Ni200) was assessed in fast pyrolysis bio-oil produced from pyrolysis of high ash and high moisture forest residue biomass. Sample mass change, ICP-MS and post-exposure electron microscopy characterization was used to investigate the extent of corrosion. Among the tested samples, type 430F and type 316 stainless steels (SS430F and SS316) and Ni200 (~98.5% Ni) showed minimal mass changes (less than 2 mg∙cm−2) after the bio-oil exposures at 50 and 80 °C for up to 168 h. SS304 was also considered to be compatible in the bio-oil due to its relatively low mass change (1.6 mg∙cm−2 or lower). SS410 samples showed greater mass loss values even after exposures at a relatively low temperature of 35 °C. Fe/Cr values from ICP-MS data implied that Cr enrichment in stainless steels would result in a protective oxide layer associated with corrosion resistance against the bio-oil. Post exposure characterization showed continuous and uniform Cr distribution in the surface oxide layer of SS430F, which showed a minimal mass change, but no oxide layer on a SS430 sample, which exhibited a significant mass loss.
Physical Education and Development of Locomotion and Gross Motor Skills of Children with Autism Spectrum Disorder
Authors: Kaplánová Adriana , Šišková Nikola , Grznárová Tatiana , Vanderka Marián
Published: December 2022

Movement abnormalities are a common problem in children with autism spectrum disorder (ASD), which affect their fine and gross motor skills, locomotion, and eye movements, along with their ability to conduct more complex movement types. The purpose of this study was to determine whether regular exercises in physical education classes using the Test of Gross Motor Development Second Edition (TGMD-2) improve locomotion, gross motor skills, and overall movement performance in children with ASD and eliminate the occurrence of movement abnormalities. Twenty children aged 5–10 years (M ± SD; 7.51 ± 1.58 years) who were diagnosed with ASD participated in the research. The TGMD-2 training program was applied for a period of 8 weeks with a frequency setting of two times a week and a duration of 30 min under the guidance of a physical education teacher. Group A exercised according to TGMD-2 instructions, while Group B was the control group, then vice versa. The rest period between exercises was 13 weeks. The research results indicate that the use of exercises to develop the motor performance of children with ASD contributed to the significant development of their locomotion and gross motor skills. In both groups A and B, we noted an improvement in locomotion (p < 0.01) and gross motor skills (p < 0.01). The results demonstrated a significant improvement in gains between the control and experimental periods in groups A (p < 0.001) and B (p < 0.001). During the 13-week rest period between exercises, we found a decrease in the level of motor performance in both groups of children with ASD (p < 0.01). In group A, we found a decrease in motor performance (p < 0.01), locomotion (p < 0.01), and gross motor skills (p < 0.01), and in group B, a significant deterioration of motor performance in terms of the total TGMD-2 score (p < 0.05). Regular movement intervention is very important for children with ASD; otherwise, their level of motor performance can drop significantly. Therefore, we recommend implementing TGMD-2 exercises as part of the physical education of children with ASD and supporting the routine and healthy habits of children.
Sustainable Entrepreneurship as a Field of Knowledge: Analyzing the Global South
Authors: Contreras Francoise , Dornberger Utz
Published: December 2022

The objective of this study is to characterize the contribution to sustainable entrepreneurship as a field of knowledge from developing countries, also called the Global South, through the analysis of the literature that has been produced in the last two decades. This research starts from the premise of the dominance of the Global North over academic production on this topic and analyzes the consequences for the Global South. Through VOSViewer software, and Biblioshiny, a web interface of bibliometrix R-package, 1964 articles that were retrieved from the WoS database were analyzed. According to the results, the dominance of the Global North is confirmed, not only by the number of articles (63% vs. 22% of the Global South), but also by the impact on the publications, the publishing systems, and the thematic addressed, among other indicators. Likewise, the low North–South collaboration (15%), and the scarce collaboration networks between Southern countries, were also confirmed. This situation may have affected the formation of a critical mass of Southern researchers to develop their own concepts and address subjects related to sustainable entrepreneurship that are more adjusted to their reality. We did not find significant differences between the Southern and the Northern research themes or the emergence of new concepts from the Global South, despite their different conditions. Finally, a closer look at the thematic trajectory in terms of scholarly production shows a lesser emphasis on sustainability in the Global South than that in the Global North. These findings are discussed herein.
Long-Term Cross-Slope Variation in Highways Built on Soft Soil under Coupling Action of Traffic Load and Consolidation
Authors: Jia Miao , Xu Jinliang , Gao Chao , Mu Minghao , E Guangxun
Published: December 2022

The variation in road cross slope with service life affects the pavement drainage and has an adverse effect on vehicle operation safety. This paper describes a cross-slope variation prediction method influenced by the coupling effect of traffic load and soil consolidation, considering characteristics of embankment to cover the shortage for insufficient consideration of compacted embankment. First, the traffic load-induced settlement equation of a highway on soft soil foundation was introduced, which considers the effects of traffic load stress, confining pressure, soil structure, strength weakening and cyclic loading times on different positions along the cross-section. Then, the finite element model of a highway on soft soil foundations under soil consolidation is established, considering the influence of soil seepage. Finally, predictions of long-term settlement and cross-slope variation generated by coupling action of traffic load and soil consolidation were carried out with contrastive analysis with measured data. We find the following: (1) the long-term settlement was mostly from the consolidation of natural soft subsoil, while the cross-slope variation was mainly affected by traffic load; (2) variation in the cross slope of highway in soft soil areas mainly occurs within 1 year of operation. The effect of passenger cars and trucks on cross-slope variation shows diametrically opposite results, as the passenger car lane decreases while the truck lane increases; (3) the relative error of the cross-slope variation prediction results with the measured data are 2.86% and 2.5% for the left and right lane cross slopes, respectively.
Analysis of Regional Social Capital, Enterprise Green Innovation and Green Total Factor Productivity—Based on Chinese A-Share Listed Companies from 2011 to 2019
Authors: Sun Huanan , Zhu Lianmei , Wang Anqi , Wang Shali , Ma Haijing
Published: December 2022

At present, social capital is considered to be one of the important reasons for promoting economic development and causing regional economic differences, but in the existing research, there is little literature on the impact of regional social capital on enterprises’ green innovation behavior and green total factor productivity (GTFP), so this paper aims to enrich the research in this area. This paper builds a regional social capital evaluation index system and uses the super-SBM model to measure the enterprise GTFP. Then, this paper brings regional social capital, enterprise green innovation and GTFP into a unified framework for the first time and further reveals the quantitative relationship between the three by using OLS and Tobit two-step methods based on the panel data of 30 provinces from 2011 to 2019. The results show that regional social capital has a positive effect on enterprise GTFP and green innovation (except for strategic green innovation output), enterprise green innovation output has a positive role in promoting GTFP, and enterprise green innovation capital investment has a masking effect between regional social capital and GTFP. Furthermore, the expansive study finds that there are differences in the impact of regional social capital on green innovation and the GTFP of heterogeneous enterprises, and financing constraints have a positive regulatory effect on the relationship between regional social capital and the GTFP of state-owned enterprises, while having an inhibitory effect on the GTFP of private enterprises. Fiscal decentralization has a partial mediating effect between regional social capital and enterprise GTFP, while urbanization and CO2 emissions have a masking effect. Additionally, this paper aims to provide a reference for the improvement of regional social capital theory, the strategic choice of green innovation of enterprises, and the high-quality development of the economy.
Measures to Ensure the Sustainability of Information Systems in the COVID-19 Environment
Authors: Kwon Hyukjin , Shin Youngjoo , Jeong Jaeyeong , Kim Kookjin , Shin Dongkyoo
Published: December 2022

National defense requires uninterrupted decision-making, even under direct or indirect impacts of non-traditional threats such as infectious diseases. Since all work utilizes information systems, it is very important to ensure the sustainability and availability of information systems. In particular, in terms of security management, defense work is being performed by dividing the network into a national defense network and a commercial Internet network. This study suggests a work execution plan for sustainability that takes into account the efficiency of work performed on the Internet and the effectiveness of security through effective defense information system operation. It is necessary to minimize the network contact points between the national defense network and the commercial Internet and to select high-priority tasks from various tasks and operate them efficiently. For this purpose, actual cases were investigated for an institution, “Organization A”, and characteristics were presented. Through the targeted tasks and operation plans presented in this paper to improve the effectiveness of defense tasks and ensure security, it will be possible to increase the sustainability and availability of task performance even under non-traditional threats such as infectious diseases.
Explore U.S. Retailers’ Sourcing Strategies for Clothing Made from Recycled Textile Materials
Authors: Lu Sheng
Published: December 2022

This study explored U.S. retailers’ sourcing patterns for clothing made from recycled textile materials. Based on a statistical analysis of over 3000 such clothing items for sale in the U.S. retail market from January 2019 to August 2022 at the Stock Keeping Unit (SKU) level, the study found that U.S. retailers adopted a diverse sourcing base for clothing made from recycled textile materials, covering developed and developing economies worldwide. Additionally, an exporting country’s economic development level and geographic location had statistically significant impacts on U.S. retailers’ sourcing patterns for clothing made from recycled textile materials regarding assortment diversity, product sophistication, market segments, and pricing. The study’s findings revealed the broad supply base for clothing made from recycled textile materials and suggested promising sourcing opportunities for such products. The findings also indicated that sourcing clothing made from recycled textile materials may help U.S. retailers achieve business benefits beyond the positive environmental impacts.
An Introductory Review of Input-Output Analysis in Sustainability Sciences Including Potential Implications of Aggregation
Authors: Bunsen Jonas , Finkbeiner Matthias
Published: December 2022

Input-output analysis has become a widely established method in sustainability sciences. It is primarily used in macroeconomic footprint analyses for allocating an economy’s externalities among the agents in that economy based on the agents’ input-output interdependencies. However, databases for input-output analyses are commonly compiled by aggregating data. Aggregation of input-output data inevitably leads to a loss of information and in some instances can lead to misinformed decision-making. The goal of this paper is to provide a simple hands-on numerical introduction to input-output analysis including the potential implications of data aggregation in an original manner. First, the calculation of production-based and consumption-based inventories is introduced based on a dummy 2 × 2 input-output table. Next, the inventories of the 2 × 2 input-output table are compared with the production-based and consumption-based inventories of a corresponding non-aggregated 4 × 4 input-output table. A comparison of the inventories of both dummy input-output tables allows for an exemplary demonstration of inaccurate allocation as a result of data aggregation and to conclude on potential implications for decision-making. Overall, this work offers a succinct and numerically substantiated introductory review of input-output analysis for practitioners in sustainability sciences including the potential implications of aggregation of input-output data. Its simplistic approach sets this work apart from other publications on aggregation in input-output analysis that are founded in economics or econometrics.
Impact of Trade Policy Uncertainty and Sustainable Development on Medical Innovation for Developed Countries: An Application of DID Approach
Authors: Shabbir Muhammad Nadir , Arshad Muhammad Usman , Alvi Muhammad Amir , Iftikhar Kainat
Published: December 2022

Covering the period from 1980 through 2020, with an emphasis on COVID-19, this paper analyzes how trade policy uncertainty and sustainable development policies affected investment in medical innovation. In a twofold difference-in-differences (DiD) approach, using autoregressive distributed lag (ARDL), the paper takes account of exogenous and heterogeneous exposure to trade policy uncertainty and trade policy adjustment in developing nations, which limited tariff increases on imported products. Both long- and short-term effects have been analyzed. Beyond patent applications, margin responses, and exports, the study indicates that eliminating tariff uncertainty boosts innovation. Developing countries have had little effect on the long-term ramifications of sectoral innovation patterns, political shifts, and imported technology. A negative response to the innovation shock and a positive response by R&D corroborate bidirectional and unidirectional causality, respectively. They demonstrate a long-term link between medical innovation, trade policy uncertainty, and R&D spending. As regards sustainable development, GDP growth and HDI have positive, and GINI index and CO2 emissions, have negative long-run relations with medical innovation. This study contributes to the literature on innovation and policy uncertainty together with sustainable development factors in developed countries, and especially on innovation trends in the medical sector, where there is a current policy ambiguity regarding the influx of foreign technology and its significance.
Energy Management Strategy for Seaport Integrated Energy System under Polymorphic Network
Authors: Teng Fei , Zhang Qing , Zou Tao , Zhu Jun , Tu Yonggang , Feng Qian
Published: December 2022

This paper studies the energy management problem of a seaport integrated energy system under the polymorphic network. Firstly, with the diversity of energy devices, a seaport integrated energy system based on the polymorphic network is established to ensure information exchange and energy interaction between heterogeneous devices, including the service layer, control layer, and data layer. Secondly, by analyzing the characteristics of different loads and the energy conversion hub, such as the power to gas (P2G) and combined cooling heating and power (CCHP), the energy management model for the seaport integrated energy system is constructed. Finally, we obtain the optimal solution by mixed integer linear programming, and the proposed strategy is used to a seaport integrated energy system including CCHP, P2G, clean energy and energy storage device. By comparing four different cases, the simulation results show a reduction in the cost of energy purchase and carbon emissions when applying our strategy with various device types and device failures. Moreover, considering the application of the proposed energy management strategy under seasonal variations, the optimal solution for the energy management problem of the seaport integrated energy system is obtained.
Crashworthiness and Failure Analyses of FRP Composite Tubes under Low Velocity Transverse Impact
Authors: Wei Guangkai , Fu Kunkun , Chen Yuan
Published: December 2022

Currently, FRP composite tubes are drawing increasing attention in many industrial applications, due to their excellent mechanical and lightweight properties, with reduced energy consumption and enhanced sustainability. This study investigates the failure mechanisms and crashworthiness performance of glass and carbon fibre reinforced polymer (GFRP and CFRP) composite tubes under low velocity transverse impact. Finite element methods were developed to establish numerical models to predict the failure responses of FRP composite tubes with a complex ply sequence of both woven and unidirectional layers. In the modelling, continuum damage mechanics and cohesive zone method were used to calculate the intralaminar and interlaminar failure behaviours, respectively, in FRP composite tubes. The numerical models were validated by corresponding experiments, and the effects of the impact energy and material type were investigated. The experimental results show that the initial impact energy does not significantly affect the specific energy absorption (SEA) and peak force (PF) of GFRP composite tubes, and the SEA and PF are generally around 0.5 kJ/kg and 600 N, respectively, when the impact energy varies from 10 J to 50 J. Failure mechanism analyses show that GFRP tubes and CFRP tubes with totally unidirectional plies present global bending deformation with significant matrix damage, and CFRP tubes with “hybrid layer type” exhibit local penetration with severe fibre and matrix damage. The crashworthiness analyses indicate that CFRP tubes perform better in SEA while GFRP tubes possess smaller PF when subjected to low velocity transverse impact.
Experimental Investigation of Water-Retaining and Unsaturated Infiltration Characteristics of Loess Soils Imbued with Microplastics
Authors: Gu Jiahui , Chen Liang , Wan Yu , Teng Yaozong , Yan Shufa , Hu Liang
Published: December 2022

Microplastics are abundant in agricultural soils and have significant impacts on rainfall infiltration and soil water-retaining capacity. To explore the effect of microplastics on agricultural soil permeability by simulating the rainfall irrigation process, a one-dimensional vertical soil column rainfall infiltration test device was used to study the unsaturated infiltration characteristics of loess soil imbued with microplastics under rainfall conditions. The following conclusions could be obtained: the microplastic content (q), the microplastic particle size (p), and the soil density (γ) have effects on rainfall infiltration; the soil water-retaining capacity would be weakened owing to the existence of microplastics; and intermittent rainfall is preferred in agricultural irrigation. Finally, the permeability coefficient (k) and average flow rate (V) of the unsaturated soil are deduced together, and the relationship between the permeability coefficient (k) and the matrix suction (ψ) of the unsaturated loess soil containing microplastics is calculated by an example, proving good consistency between the experimental results and theoretical calculations. Microplastics represent negative effects on rainfall infiltration and soil water retention, so it is recommended to dispose of them.
Bioremediation of Crystal Violet by Organic Matter and Assessment of Antimicrobial Properties of the Obtained Product
Authors: Chwastowski Jarosław , Staroń Paweł , Pięta Ewa , Paluszkiewicz Czesława
Published: December 2022

The study investigated the waste beet pulp shreds for the use as a sorbent for removing crystal violet dye from aqueous solutions and investigating the antimicrobial properties of the obtained material. During the preparation of the BPSCV (beet pulp shreds with adsorbed crystal violet) material, the equilibrium and kinetic studies of the crystal violet dye (CV) sorption process on BPS were carried out. The equilibrium tests allowed for the selection of the best-fitted isotherm model and the determination of the sorption capacity of the material. It turned out that the Langmuir isotherm model had the best fit (R2 > 0.98) and the sorption capacity equaled 28.07 mg/g. The pseudo-second-order model R2 > 0.999 (obtained from kinetic studies) and FT-IR analysis confirmed that the sorption process of the CV on BPS is chemical. The minimal growth inhibition antimicrobial tests showed that the obtained material inhibits the growth of chosen microorganisms. Escherichia coli (MIC = 500 ppm) and Pseudomonas aeruginosa (MIC = 300 ppm) are more resistant to BPSCV than Candida albicans and Staphylococcus aureus (MIC = 100 ppm).
Scoping Review (SR) via Text Data Mining on Water Scarcity and Climate Change
Authors: Aversa Dario , Adamashvili Nino , Fiore Mariantonietta , Spada Alessia
Published: December 2022

Climate change is causing the risk of weather events and instable water accessibility, making water insufficiency a serious problem. According to the 2022 Intergovernmental Panel on Climate Change (IPCC), 70% of extreme weather events such as droughts and floods have been water-related in the last 15 years. Since the climate change processes are speeding up, this percentage is expected to increase. A plethora of researchers have been working on the correlation between water scarcity and climate change. The purpose of this paper is to examine the published research dealing with water scarcity and climate. Therefore, the study carries out a scoping review (SR) via text data mining and reveals the related topics. Two kinds of analysis were carried out using IRaMuTeQ software: descriptive analysis (TTR, Giraud index, Herdan index and Zipf’s curve) and cluster analysis (Reinert’s method). The results show that the topic of water scarcity refers to the direct and indirect economic impacts on its availability for irrigation, the willingness to pay more for an irrigation water supply and the role of public institutions in “achieving sustainable development goals”. The conclusion of the paper highlights the role of this analysis for developing future research and identifies implications for theory, practice and policy in order to overcome the current global challenges related to water scarcity and climate change.
The Limit of Urban Land Expansion Based on Population Growth and Economic Development: A Case Study of Shandong Province in China
Authors: Wang Xiaoming , Chen Bocheng , Dong Qianqian
Published: December 2022

As a developing country, China is experiencing rapid urbanization. With rapid economic development and urban population growth, urban land continues to expand. The urban land expansion provides development space for cities; however, the disorderly expansion of urban land also results in a significant waste of land resources. In order to effectively regulate the scale of urban land and prevent the disorderly expansion of urban land, it is necessary to conduct analyses of the characteristics and trends of urban land expansion. In the present paper, taking Shandong province as the research area, we analyze the characteristics and limits of urban land expansion. Based on the relationship between urban land expansion, economic development, and urban population growth, using urban land area, the output value of secondary and tertiary industries, and population data to construct a marginal effect model and logistic model to estimate the limit time and limit scale of urban land expansion in Shandong province from the perspectives of economic development and urban population growth. The results show that: (a) Economic development and urban population growth are the main influencing factors of urban land expansion in Shandong province. With the development of the economy and urbanization, the expansion rate of urban land in Shandong province is decreasing. (b) From the perspective of economic development, With the continuous improvement of urban land use efficiency, the demand for newly-added urban land by economic development gradually weakens. In 2033, the urban land in Shandong province will reach the expansion limit, with a limit scale of 7982 km2. (c) From the perspective of urban population growth, in 2037, the urbanization rate of Shandong province will reach 80%, the urban population will be stable, and the urban land will reach the expansion limit, with a limit scale of 9068.8 km2.
Short-Term Traffic Congestion Prediction Using Hybrid Deep Learning Technique
Authors: Anjaneyulu Mohandu , Kubendiran Mohan
Published: December 2022

A vital problem faced by urban areas, traffic congestion impacts wealth, climate, and air pollution in cities. Sustainable transportation systems (STSs) play a crucial role in traffic congestion prediction for adopting transportation networks to improve the efficiency and capacity of traffic management. In STSs, one of the essential functional areas is the advanced traffic management system, which alleviates traffic congestion by locating traffic bottlenecks to intensify the interpretation of the traffic network. Furthermore, in urban areas, accurate short-term traffic congestion forecasting is critical for designing transport infrastructure and for the real-time optimization of traffic. The main objective of this paper was to devise a method to predict short-term traffic congestion (STTC) every 5 min over 1 h. This paper proposes a hybrid Xception support vector machine (XPSVM) classifier model to predict STTC. Primarily, the Xception classifier uses separable convolution, ReLU, and convolution techniques to predict the feature detection in the dataset. Secondarily, the support vector machine (SVM) classifier operates maximum marginal separations to predict the output more accurately using the weight regularization technique and a fine-tuned binary hyperplane mechanism. The dataset used in this work was taken from Google Maps and comprised snapshots of Bangalore, Karnataka, taken using the Selenium automation tool. The experimental outcome showed that the proposed model forecasted traffic congestion with an accuracy of 97.16%.
Source Apportionment and Risk Assessment of Soil Heavy Metals due to Railroad Activity Using a Positive Matrix Factorization Approach
Authors: Wang Zhen , Zhang Jianqiang , Watanabe Izumi
Published: December 2022

The effects of railway operation on soil environments are an important topic. In this research, soil samples were collected from two diesel-driven railways and two electric railways in Japan. A positive matrix factorization (PMF) model was applied to investigate the sources of eight heavy metals in the soil near the railways. The results showed that railway operation was the dominant anthropogenic source of heavy metals in the soil in the study areas among five potential sources, with contributions ranging from 11.73% to 42.55%. Compared with that of electricity-driven railways, the effect of diesel-driven railways was larger. The environmental risk-assessment analysis suggested that the soils near the selected railways fall within the weak-to-extremely strong contamination category, and experienced moderate-to-extremely strong ecological risk. A health risk assessment revealed that the soil presented both noncarcinogenic and carcinogenic risks for children, with ingestion as the principal exposure pathway. The PMF-Environment Risk Assessment and PMF-Human Health Risk Assessment models were developed to obtain the ecological and human health risks for every source category. Railway operation was regarded as the major factor influencing ecology and human health at the diesel-driven railway sampling sites. However, at electricity-driven railway sampling sites, natural sources were dominant.
Do the Chinese Government’s Efforts to Make a Low-Carbon Industrial Transition Hinder or Promote the Economic Development? Evidence from Low-Carbon Industrial Parks Pilot Policy
Authors: Li Zhengbo , Deng Feng , Zhu Qiaoqiao , Cao Li , Jiang Yunyan
Published: December 2022

Under the background of “peak carbon dioxide emissions” and “carbon neutrality” strategy, it is urgent to explore whether China’s great efforts to continuously promote industrial low-carbon transition can promote high-quality economic development. Taking the implementation of low-carbon industrial parks pilot policy (LIPPP) as a “quasi-natural experiment”, this paper tries to answer this question. The results show that the LIPPP doesn’t significantly promote the sustainable-oriented high-quality development (SHD) of the economy, but mainly boosts the value-oriented high-quality development (VHD), which is characterized by being obviously biased towards the technological progress. The policy effect is more obvious in the central region and cities with a relatively poor natural resource endowment. The mechanism analysis shows that the LIPPP promotes the VHD of the economy through the innovation incentive effect and the capital deepening effect. The technological progress related to the VHD promoted by the LIPPP has a crowding out effect on that of the SHD. In addition, regional innovation, capital deepening, and energy transformation all play a certain role in promoting the SHD, but which is overshadowed by the effect of the VHD promoted by the LIPPP. This paper provides policy implications for China to promote high-quality economic development in the process of low-carbon transition.
Exact Solutions for the Generalized Atangana-Baleanu-Riemann Fractional (3 + 1)-Dimensional Kadomtsev–Petviashvili Equation
Authors: Hong Baojian , Wang Jinghan
Published: December 2022

In this article, the generalized Jacobi elliptic function expansion method with four new Jacobi elliptic functions was used to the generalized fractional (3 + 1)-dimensional Kadomtsev–Petviashvili (GFKP) equation with the Atangana-Baleanu-Riemann fractional derivative, and abundant new types of analytical solutions to the GFKP were obtained. It is well known that there is a tight connection between symmetry and travelling wave solutions. Most of the existing techniques to handle the PDEs for finding the exact solitary wave solutions are, in essence, a case of symmetry reduction, including nonclassical symmetry and Lie symmetries etc. Some 3D plots, 2D plots, and contour plots of these solutions were simulated to reveal the inner structure of the equation, which showed that the efficient method is sufficient to seek exact solutions of the nonlinear partial differential models arising in mathematical physics.
Editorial for Special Issue Feature Papers 2020
Authors: Odintsov Sergei D.
Published: December 2022

This issue of featured papers from 2020 is related to the study of symmetry phenomena in various different fields, but mainly in theoretical physics [...]