bluuebunny/crossref_metadata_2025 huggingface dataset:
Information Leakage in Deep Learning-Based Hyperspectral Image Classification: A Survey
Authors: Feng Hao , Wang Yongcheng , Li Zheng , Zhang Ning , Zhang Yuxi , Gao Yunxiao
Published: July 2023

In deep learning-based hyperspectral remote sensing image classification tasks, random sampling strategies are typically used to train model parameters for testing and evaluation. However, this approach leads to strong spatial autocorrelation between the training set samples and the surrounding test set samples, and some unlabeled test set data directly participate in the training of the network. This leaked information makes the model overly optimistic. Models trained under these conditions tend to overfit to a single dataset, which limits the range of practical applications. This paper analyzes the causes and effects of information leakage and summarizes the methods from existing models to mitigate the effects of information leakage. Specifically, this paper states the main issues in this area, where the issue of information leakage is addressed in detail. Second, some algorithms and related models used to mitigate information leakage are categorized, including reducing the number of training samples, using spatially disjoint sampling strategies, few-shot learning, and unsupervised learning. These models and methods are classified according to the sample-related phase and the feature extraction phase. Finally, several representative hyperspectral image classification models experiments are conducted on the common datasets and their effectiveness in mitigating information leakage is analyzed.
An SAR Image Automatic Target Recognition Method Based on the Scattering Parameter Gaussian Mixture Model
Authors: Qin Jikai , Liu Zheng , Ran Lei , Xie Rong , Tang Junkui , Zhu Hongyu
Published: July 2023

General synthetic aperture radar (SAR) image automatic target recognition (ATR) methods perform well under standard operation conditions (SOCs). However, they are not effective in extended operation conditions (EOCs). To improve the robustness of the ATR system under various EOCs, an ATR method for SAR images based on the scattering parameter Gaussian mixture model (GMM) is proposed in this paper. First, an improved active contour model (ACM) is used for target–background segmentation, which is more robust against noise than the constant false alarm rate (CFAR) method. Then, as the extracted attributed scattering center (ASC) is sensitive to noise and resolution, the GMM is constructed using the extracted ASC set. Next, the weighted Gaussian quadratic form distance (WGQFD) is adopted to measure the similarity of GMMs for the recognition task, thereby avoiding false alarms and missed alarms caused by the varying number of scattering centers. Moreover, adaptive aspect–frame division is employed to reduce the number of templates and improve recognition efficiency. Finally, based on the public measured MSTAR dataset, different EOCs are constructed under noise, resolution change, model change, depression angle change, and occlusion of different proportions. The experimental results under different EOCs demonstrate that the proposed method exhibits excellent robustness while maintaining low computation time.
Air Temperature Monitoring over Low Latitude Rice Planting Areas: Combining Remote Sensing, Model Assimilation, and Machine Learning Techniques
Authors: Lin Minghao , Fang Qiang , Xia Jizhe , Xu Chenyang
Published: July 2023

Air temperature (Ta) is essential for studying surface processes and human activities, particularly agricultural cultivation, which is strongly influenced by temperature. Remote sensing techniques that integrate multi-source data can estimate Ta with a high degree of accuracy, overcoming the shortcomings of traditional measurements due to spatial heterogeneity. Based on in situ measurements in Guangdong Province from 2012 to 2018, this study applied three machine learning (ML) models and fused multi-source datasets to evaluate the performance of four data combinations in Ta estimation. Correlations of covariates were compared, focusing on rice planting areas (RA). The results showed that (1) The fusion of multi-source data improved the accuracy of model estimations, where the best performance was achieved by the random forest (RF) model combined with the ERA5 combination, with the highest R2 reaching 0.956, the MAE value of 0.996 °C, and the RMSE of 1.365 °C; (2) total precipitation (TP), wind speed (WD), normalized difference vegetation index (NDVI), and land surface temperature (LST) were significant covariates for long-term Ta estimations; (3) Rice planting improved the model performance in estimating Ta, and model accuracy decreased during the crop rotation in summer. This study provides a reference for the selection of temperature estimation models and covariate datasets. It offers a case for subsequent ML studies on remote sensing of temperatures over agricultural areas and the impact of agricultural cultivation on global warming.
Accuracy Improvement of High-Resolution Wide-Swath Spaceborne Synthetic Aperture Radar Imaging with Low Pule Repetition Frequency
Authors: Wang Xiaofeng , Ruan Yaduan , Zhang Xinggan
Published: July 2023

For a single-channel spaceborne synthetic aperture radar (SAR), the usage of a low pulse repetition frequency (PRF) is an effective technical way to extend the range swath. The sub-aperture imaging strategy is usually used to solve the problem of azimuth spectrum aliasing under the condition of a low PRF. However, the required up-sampling processing before the coherent synthesis of sub-images will lead to spectrum discontinuity between adjacent sub-images, which leads to an obvious grating lobe phenomenon after the process of sub-image synthesis, resulting in a significant decrease in image quality. For this issue, a high-resolution wide-swath (HRWS) imaging algorithm for a spaceborne SAR with a low PRF is proposed in this paper based on optimal spectrum shift processing. First, each sub-aperture is imaged using the typical range migration algorithm (RMA), and then all sub-images are up-sampled at the same time. Then, based on the criterion of the minimum grating lobe, the optimal spectrum shift is estimated. Finally, the spectrum of all sub-images is shifted and then all the shifted sub-images are synthesized coherently. The simulation data processing results verify the effectiveness of the proposed method.
Investigating Factors for Travelers’ Parking Behavior Intentions in Changchun, China, under the Influence of Smart Parking Systems
Authors: Zhang Yunxiang , Song Xianmin , Tao Pengfei , Li Haitao , Zhan Tianshu , Cao Qian
Published: July 2023

Unraveling the determinants of travelers’ parking behavior intentions is critical to the widespread adoption of smart parking systems (SPSs), which hold the promise of greatly enhancing parking efficiency and optimizing resource allocation within urban spaces. Our study pioneers the use of an integrated methodology combining structural equation modeling (SEM) and hierarchical regression modeling (HRM) to dissect the complex interplay of these determinants. We found that, in the structural equation model, social influence notably stood out as having the most significant impact on the intention to utilize SPSs. Notably, while perceived privacy concerns may have ranked lower in terms of influence among these factors, their role was relatively crucial, particularly given the contemporary emphasis on data security. Moreover, within the hierarchical regression model, driving experience was found to play a crucial role in determining the intention to use SPSs. Equally important, our research revealed a divergence in parking intentions between individuals with children and those without. This points towards the imperative need for personalized strategies that can cater to the diverse requirements of different user demographics. This research offers guidance for operators of SPSs aiming to formulate targeted approaches.
Impact of Hotel Employees’ Psychological Well-Being on Job Satisfaction and Pro-Social Service Behavior: Moderating Effect of Work–Life Balance
Authors: Jung Hyo-Sun , Hwang Yu-Hyun , Yoon Hye-Hyun
Published: July 2023

This study investigates how deluxe hotel employees’ perceptions of their own psychological well-being impact their job satisfaction and pro-social service behavior. It also examines the moderating effect of work–life balance on the relationship between psychological well-being and job satisfaction. A self-administered questionnaire was distributed to 275 deluxe hotel employees using convenience sampling. First, of the studied sub-factors of employee psychological well-being, positive relationships increased job satisfaction the most, followed by self-acceptance, purpose in life, and environmental mastery. Second, deluxe hotel employees’ job satisfaction positively impacted their pro-social service behavior. Third, the positive effect of one sub-factor of psychological well-being, purpose in life, had a stronger impact on job satisfaction in respondents with high levels of work–life balance. Theoretical and practical implications, as well as limitations and future research directions, are discussed.
Interaction Patterns of Motorists and Cyclists at Intersections: Insight from a Vehicle–Bicycle Simulator Study
Authors: Zhang Meng , Quante Laura , Gröne Kilian , Schießl Caroline
Published: July 2023

At intersections, road users need to comprehend the intentions of others while also implicitly expressing their own intentions using dynamic information. Identifying patterns of this implicit communication between human drivers and vulnerable road users (VRUs) at intersections could enhance automated driving functions (ADFs), enabling more human-like communication with VRUs. To this end, we conducted a coupled vehicle–bicycle simulator study to investigate interactions between right-turning motorists and crossing cyclists. This involved 34 participants (17 pairs of motorists and cyclists) encountering each other in a virtual intersection. The analysis focused on identifying interaction patterns between motorists and cyclists, specifically aiming to discern which patterns were more likely to be accepted by both parties. We found that in CM (vehicles overtaking), the post-encroachment time (PET) and the average speed of vehicles were higher than in the other two interaction patterns: C (bicycles always in front) and CMC (bicycles overtake). However, subjective ratings indicated that CM was viewed as more critical and less cooperative. Furthermore, this study unveiled the influence of crossing order and overtaking position on subjective ratings through ordered logistic regressions, suggesting that earlier overtaking could improve cyclists’ acceptance of the interaction. These findings may contribute to the optimization of communication strategies for ADF, thereby ensuring safety in interactions with VRUs.
Effects of the Integrated Use of Dairy Cow Manure on Soil Properties and Biological Fertility
Authors: Han Ziyu , He Wenjun , Shi Huading , Wang Chen , Liu Chenfeng , Feng Yao
Published: July 2023

The appropriate use of manure is important for the sustainable development of dairy farms. To identify more advantageous ways of using manure and key factors in the recycling process, this study investigated differences in soil fertility between solid and liquid manure waste recycling at an integrated farm. Both types of manure waste recycling promote soil fertility. However, solid manure exerted a more pronounced effect on soil fertility, especially on available phosphorus (P), which increased by 93.83%, but only 26.67% with liquid manure. As the amount of solid manure was increased, a clear logarithmic relationship (correlation coefficient = 0.90) formed between manure use and available P, indicating that P was a key index for manure recycling. Solid manure had a more positive influence on soil fertility in terms of microbial community change, as revealed by redundancy analysis and Pearson’s correlation analysis. The results of this study can be applied to most large-scale breeding farms, that the combination of solid and liquid manure fertilizer can be used to meet sustainable development goals. And the findings highlight solid manure as a key component for improving soil fertility.
Historic Graffiti as a Visual Medium for the Sustainable Development of the Underground Built Heritage
Authors: Trentin Mia Gaia , Altaratz Doron , Caine Moshe , Re’em Amit , Tinazzo Andrea , Gasanova Svetlana
Published: July 2023

Since prehistoric times, graffiti has been a way for humans to express themselves and interact with the landscape in a visual way. Graffiti is a visual record of the relationship between society, culture, and the environment over time, representing an additional layer of sociocultural value to the underground built heritage (UBH). Thanks to the application of digital technologies and a specific workflow, this paper will suggest how graffiti can be regarded as an additional and relevant element of creating connections and strengthening the site’s values, bridging the past and present communities. Through the critical discussion of two case studies—the monastery of Ayia Napa (Cyprus) and the Saint Helena chapel in the Holy Sepulchre in Jerusalem—the authors want to achieve two main goals: first, they want to highlight the sociocultural value and raise awareness about the presence and significance of historic graffiti. In the second instance, they wish to illustrate how graffiti can be an additional agent for the sustainable development, valorization, and promotion of the UBH.
Environmental Sustainability of Metaverse: Perspectives from Romanian Developers
Authors: Vlăduțescu Ștefan , Stănescu Georgiana Camelia
Published: July 2023

The metaverse is currently in the process of development and has applications in various fields, ranging from the gaming industry to art, communication, education, and fashion. Researchers regard the metaverse as the future of the internet, and, in this context, the impact of this new universe’s development on the environment needs to be investigated to find viable solutions for its sustainability. We have discussed the economic and social sustainability consequences of the metaverse, and we have largely concentrated on the environmental effects. In conducting this research, we used a quantitative methodology mainly based on a structured questionnaire. We analyzed the impact of the metaverse on the environment from the perspective of professionals in the Romanian software development and programming industries. We selected this sample because the field is newly emerging and because they are experts on how the metaverse functions and evolves. We concluded that IT professionals believe that the new universe could have several negative impacts on the natural environment, such as increased power consumption or increased CO2. emissions and the negative impact can be mitigated by adopting clear regulations and sustainable policies at the international level. This study aims to contribute to the long-term sustainability of the metaverse ecosystem by facilitating a comprehensive understanding of its functioning and evolution, as well as by addressing potential negative impacts on the natural environment. Additionally, the study seeks to make a scholarly contribution to advancing a sustainable metaverse by fostering informed decision-making processes and encouraging responsible practices within the industry. This research might be useful for technology companies, academics, and policymakers.
Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey
Authors: Abdalzaher Mohamed , Krichen Moez , Yiltas-Kaplan Derya , Ben Dhaou Imed , Adoni Wilfried
Published: July 2023

Earthquake early warning systems (EEWS) are crucial for saving lives in earthquake-prone areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a sustainable EEWS that is capable of providing early warning to people and coordinating disaster response efforts. To achieve this goal, we provide an overview of the fundamental concepts of seismic waves and associated signal processing. We then present a detailed discussion of the IoT-enabled EEWS, including the use of IoT networks to track the actions taken by various EEWS organizations and the cloud infrastructure to gather data, analyze it, and send alarms when necessary. Furthermore, we present a taxonomy of emerging EEWS approaches using IoT and cloud facilities, which includes the integration of advanced technologies such as machine learning (ML) algorithms, distributed computing, and edge computing. We also elaborate on a generic EEWS architecture that is sustainable and efficient and highlight the importance of considering sustainability in the design of such systems. Additionally, we discuss the role of drones in disaster management and their potential to enhance the effectiveness of EEWS. Furthermore, we provide a summary of the primary verification and validation methods required for the systems under consideration. In addition to the contributions mentioned above, this study also highlights the implications of using IoT and cloud infrastructure in early earthquake detection and disaster management. Our research design involved a comprehensive survey of the existing literature on early earthquake warning systems and the use of IoT and cloud infrastructure. We also conducted a thorough analysis of the taxonomy of emerging EEWS approaches using IoT and cloud facilities and the verification and validation methods required for such systems. Our findings suggest that the use of IoT and cloud infrastructure in early earthquake detection can significantly improve the speed and effectiveness of disaster response efforts, thereby saving lives and reducing the economic impact of earthquakes. Finally, we identify research gaps in this domain and suggest future directions toward achieving a sustainable EEWS. Overall, this study provides valuable insights into the use of IoT and cloud infrastructure in earthquake disaster early detection and emphasizes the importance of sustainability in designing such systems.
Neo-Extractivism and Formalization of Artisanal and Small-Scale Mining—The Case of the Santurbán Moorland (Colombia)
Authors: Zárate Rueda Ruth , Beltrán Villamizar Yolima Ivonne , Becerra Ardila Luis Eduardo
Published: July 2023

The purpose of this paper is to analyze the negative impact of neo-extractivism to boost the mining industry and the components that prevent the formalization of ASM as a model of rural economic development in Vetas, California, Suratá, and Matanza, municipalities adjacent to the Santurbán moorland (Colombia). A qualitative methodology with ethnographic design was followed, implementing the NVivo software (v12) for the analysis of information. The results show that the neo-extractivist model stands in opposition to the formalization of ASM in the territory, which prevents the prioritization of rural economic development by regional and local governments. ASM is at a disadvantage with respect to large-scale extractive industry, although this activity has been carried out in this region for centuries; it is also under threat as a result of a delimitation process that seeks the protection of the moor ecosystem, putting at risk the economic and socio-environmental stability of the communities that depend on this activity.
The Development of Service Metrics Indicators of a Public Transportation Service Case Study: Intercity Trains in Nakhon Ratchasima Province, Thailand
Authors: Wonglakorn Nattiya , Chantaratang Anon , Suksiripattanapong Cherdsak , Na Sritha Karn , Aunphoklang Warunee , Ninjinda Nattida , Keerakittisakul Wilasinee
Published: July 2023

This research studied the relationships of indicators related to the selection of intercity train services in Thailand’s Nakhon Ratchasima province. The goal was to examine the characteristics of the intercity train services and the factors that influence choosing them. The research tool used to collect data consisted of 508 sets of questionnaires completed by samples who had used the intercity train service. The data were analyzed using structural equation modeling to investigate the service quality and customer satisfaction indicators affecting the selection of intercity train services. The study found that the service quality indicators included station, service, staff, and vehicle. The customer satisfaction indicators included station, service, travel promotions, and price satisfaction. However, when the service quality indicators were investigated, they had a direct positive effect on customer satisfaction at the 0.01 level of statistical significance. Passengers are most satisfied with obtaining travel information, such as train timetables, fares, and updated information. The involved agencies can use the study’s findings to determine policies and formulate plans for information management and intercity train service metrics.
Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate
Authors: Alsafadi Karam , Bi Shuoben , Bashir Bashar , Alsalman Abdullah , Srivastava Amit Kumar
Published: July 2023

The evaluation of bioclimatic viticulture indices (BVIs) zones, similar to any other crop, necessitates a comprehensive understanding of the spatial variability of climate data. This study focuses on assessing the suitability of BVIs in the Jabal Al Arab region, a significant viticulture area in the Eastern Mediterranean. The aim is to analyze four temperature-based bioclimatic indices and the hydrothermal coefficient (HTC) to map their patterns and spatial variation across the region under climate change scenarios. Daily temperature data from 15 meteorological stations and 57 rain gauges spanning 1984–2014 were utilized, along with downscaled future scenarios (the Representative Concentration Pathways (RCPs) based on the second generation Canadian Earth System Model (CanESM2)) for 2016–2100. Additionally, statistical analysis and hybrid interpolation (regression-kriging) were employed to accurately map the BVIs throughout the region. The results reveal substantial spatial variability in Jabal Al Arab’s climate, with heat accumulation and the hydrothermal index during the growing season significantly influenced by elevation and distance to the seacoast. Additionally, the viticulture zones vary based on the specific index used and the projected future climate scenarios compared to the current climate. Climate change projections indicate a trend toward warmer conditions in the future. Under the RCP scenarios, the region can be categorized into up to three bioclimatic classes for certain indices, in contrast to the current climate with six classes. These findings offer valuable insights into viticulture suitability within each climatic region and facilitate the identification of homogeneous zones. By employing consistent bioclimatic indices and advanced hybrid interpolation techniques, this study enables meaningful comparisons of Jabal Al Arab with other viticulture regions worldwide. Such information is crucial for selecting suitable grapevine varieties and assessing the potential for grape production in the future.
Linking Nematode Communities and Soil Health under Climate Change
Authors: Pires David , Orlando Valeria , Collett Raymond L. , Moreira David , Costa Sofia R. , Inácio Maria L.
Published: July 2023

Soil health is intimately intertwined with ecosystem services. Climate change negatively impacts ecosystem functioning, by altering carbon and nitrogen biogeochemical cycles and shifting nutrient bioavailability, thus hampering food production and exacerbating biodiversity loss. Soil ecosystem services are provided by belowground biota, and as the most abundant metazoans on Earth, nematodes are key elements of soil food webs and reliable bioindicators of soil health. Here, we carry out a literature review from 2019, the year that the Intergovernmental Panel on Climate Change published a report relating and expressing serious concerns on the effects of climate change on the land degradation and sustainability of terrestrial ecosystems. We focus on documenting and discussing the composition of nematode communities contributing to improving soil health, and soil management practices to promote their presence and limit the effects of climate change on soils. By recognizing beneficial nematodes as plant-promoting agents, we could harness their potential to our benefit, catalyze decomposition services, improve plant performance, and increase carbon sequestration. This way, we will contribute to soil health and a well-balanced and well-managed system, making it possible to increase productivity, guarantee food security, and reduce the yield gap, with a limited human footprint on the environment.
Microbial–Plant Collaborative Remediation of Cd-Contaminated Wastewater and Soil in the Surrounding Area of Nuclear Power Plants and Risk Assessment
Authors: Wei Wei , Song Yan
Published: July 2023

The continuous development of China’s nuclear industry has caused an increasingly serious problem of heavy metal pollution in the ecological environment. A survey of the current situation shows that the quality of China’s groundwater bodies and their surrounding ecological environment has been severely affected. China has started to devote more attention to the issue of nuclear emissions and pollution. In view of this, this study takes an area contaminated by nuclear power plant emissions as the object of research and uses plant–microbe synergy to remediate the cadmium-contaminated environment. Cadmium-tolerant strains were isolated from the soil and identified as Serratia marcescens. The morphological characteristics of the cadmium-tolerant strains were observed with electron microscopy in the presence or absence of cadmium ions. The removal of Cd2+ from wastewater was analyzed in four experimental groups: Cd2+ removal from Cd2+-contaminated wastewater by combining a Cd-tolerant strain with Cd-flower, Cd-tolerant strain with Cd-flower, Cd-flower with alkali treatment, and Cd-tolerant strain with alkali treatment. This study innovatively treated Cd ion concentrations of 50 mg/L, 100 mg/L, 200 mg/L, and 300 mg/L. The results showed that the cadmium-tolerant strains were more densely concentrated in the treated Phyllostachys than in the untreated condition. This indicates that the Cd-tolerant strains were effectively enhanced by the alkali treatment of Phyllostachys spp. and that the adsorption of Cd ions to the Cd-tolerant strains was improved. In the presence of Cd2+ flowers only, the best removal of Cd2+ was achieved at a concentration of 50 mg/L, with a removal rate of 74.10%; the addition of Cd-tolerant strains resulted in a removal rate of 91.21%. When the alkali treatment was applied to the flat bamboo flowers, the removal rate was 84.36% when the concentration of Cd2+ was 100 mg/L. Then, when the cadmium-tolerant strain was added to the treated flat bamboo flower group, the maximum removal rate was 89.74% when the concentration of Cd2+ was 100 mg/L. The cadmium ion content of Cd2+ increased positively with increasing experimental time. In addition, the quasi-secondary correlation coefficients for cadmium ions in Lobelia were all greater than 0.9905, indicating that the adsorption kinetics were significantly correlated with the quasi-secondary kinetics. The analysis of heavy metal enrichment in Lobelia was divided into four groups, with Lobelia showing the best tolerance and cadmium adsorption capacity at a cadmium concentration of 20 mg/L. The results of super-enrichment coefficients showed that the enrichment coefficients of Lobelia ranged from 1.03 to 1.97, with values greater than 1. All these results indicate that the combination of cadmium-tolerant strains and plants can effectively remediate nuclear-contaminated soil and wastewater, thus improving soil availability and water regeneration, and improving the human living environment.
Assessment of Outdoor Thermal Comfort in Urban Public Space, during the Hottest Period in Annaba City, Algeria
Authors: Boussaidi Karima , Djaghrouri Djamila , Benabbas Moussadek , Altan Hasim
Published: July 2023

In this study; the outdoor thermal comfort of the users of two urban plazas with different morphologies in Annaba city, Algeria, have been evaluated. First, field measurements of the microclimatic parameters took place; namely the air temperature and the relative humidity in the two urban plazas, during hot days. Then, these measurements were compared with the results of the numerical simulations carried out by ENVI-met software in order to validate the model. The outdoor thermal comfort was evaluated by microclimatic measurements as well as a questionnaire survey consisting of interviews during the measurement days. The main objective was to determine the neutral Physiological Equivalent Temperature (PET) and to examine the influence of urban microclimatic conditions on the subjective thermal perception of people, as well as to compare it with different indexes of thermal comfort. Hence, the aim was to compare the microclimatic parameters of the two plazas, with and without vegetation and to see their impact on the thermal comfort indices. The results show that there is a difference between the two morphologies. Moreover, vegetation and urban morphology influence the neutral values of the thermal comfort indices.
The Dynamic Simulation Analysis of the Impact of Urbanization and Globalization on Environmental Quality
Authors: Ozturk Ilhan , Savranlar Buket , Aslan Alper , Al-mulali Usama , Artan Seyfettin
Published: July 2023

This study aims to analyze the effect of urban population and economic globalization on air quality in Turkey for the period 1970–2017, including GDP and electricity consumption as control variables. This paper is the first attempt to apply the dynamic autoregressive-distributed lag (DARDL) approach to explore the association between carbon emissions, urbanization, economic globalization, GDP, and electricity consumption in Turkey. The analysis results suggested the existence of a cointegration relationship between all series in the long run. DARDL results revealed that while urbanization has a statistically significant effect on carbon emissions in the short or long run, economic globalization has a positive impact in the long run. That is, economic globalization increases carbon emissions by about 0.15 percent. Thus, it can be said that globalization is more critical than urbanization in terms of environmental costs. In addition, it was determined that GDP and electricity consumption increase carbon emissions in both the long and short run. Also, the response of CO2 emissions to all shocks in the explanatories was determined. All future shocks of electricity consumption lead to no change in CO2 emissions. The negative shocks of both urbanization and globalization decrease CO2 emissions in the short run, but the response of CO2 is stable in the long run. The effects of a shock in GDP are exactly the opposite.
Correlation of the Effect of Native Bioagents on Soil Properties and Their Influence on Stem Rot Disease of Rice
Authors: Vanama Sowmya , Pesari Maruthi , Rajendran Gobinath , Gali Uma Devi , Rathod Santosha , Panuganti Rajanikanth , Chilukuri Srivalli , Chinnaswami Kannan , Kumar Sumit , Minkina Tatiana , Sansinenea Estibaliz , Keswani Chetan
Published: July 2023

Soil is a crucial component for plant growth, as it provides water, nutrients, and mechanical support. Various factors, such as crop cultivation, microflora, nutrient addition, and water availability, significantly affect soil properties. Maintaining soil health is important, and one approach is the introduction of native organisms with multifaceted activities. The study evaluates the effects of introducing these microbes (Trichoderma asperellum strain TAIK1, Bacillus cabrialesii strain BIK3, Pseudomonas putida strain PIK1, and Pseudomonas otitidis strain POPS1) and their consortium, a combination of four bioagents, on soil health, plant growth, and the incidence of stem rot disease caused by Sclerotium oryzae in rice. Upon treatment of soil with the consortium of the four native bioagents mentioned above through seed treatment or soil application, variations/increases in the chemical properties of the soil were observed, viz., pH (8.08 to 8.28), electrical conductivity (EC) (0.72 to 0.75 d S m−1), organic carbon (OC) (0.57 to 0.68 %), available soil nitrogen (SN) (155 to 315 kg/ha), soil phosphorus (SP) (7.87 to 24.91 kg/ha), soil potassium (SK) (121.29 to 249.42 kg/ha), and soil enzymes (urease (0.73 to 7.33 µg urea hydrolyzed g−1 soil h−1), acid and alkaline phosphatase (0.09 to 1.39 and 0.90 to 1.78 µg of p-nitrophenol released g−1 soil h−1), and dehydrogenase (0.14 to 16.44 mg triphenyl formazan (TPF) produced g−1 soil h−1)), compared to untreated soil. Treatment of seeds with the consortium of four native bioagents resulted in a significant increase in plant height (39.16%), the number of panicles (30.29%), and average grain yield (41.36%) over control plants. Under controlled conditions, the bioagent-treated plants showed a 69.37% reduction in stem rot disease. The findings of this study indicate a positive correlation between soil properties (pH, EC, OC, SN, SP, SK, and soil enzymes) and plant growth (shoot and root length, fresh and dry weight) as well as a highly negative association of soil properties with stem rot disease severity. The results suggest that using native bioagents as a management strategy can control stem rot disease and enhance crop productivity, while reducing reliance on chemical management. These findings provide valuable insights into the development of sustainable agricultural practices that maximize productivity by minimizing negative environmental impacts, which promotes soil health, plant growth, and disease management.
Correction: Bucea-Manea-Țoniș et al. Creating IoT-Enriched Learner-Centered Environments in Sports Science Higher Education during the Pandemic. Sustainability 2022, 14, 4339
Authors: Bucea-Manea-Țoniș Rocsana , Vasile Luciela , Stănescu Rareș , Moanță Alina
Published: July 2023

The authors would like to make the following corrections to their published paper [...]
Influencing Travelers’ Behavior in Thailand Comparing Situations of during and Post COVID-19
Authors: Thotongkam Woraanong , Champahom Thanapong , Nilplub Chartaya , Wimuttisuksuntorn Warantorn , Jomnonkwao Sajjakaj , Ratanavaraha Vatanavongs
Published: July 2023

Tourism is the primary source of income for many countries, particularly developing ones. However, due to the impact of the 2019 Coronavirus epidemic, the tourism sector has been significantly affected. This study aims to identify factors that influence motivation and travel frequency. Two scenarios were compared: during COVID-19 and post-COVID-19. The questionnaire was developed based on the Health Belief model. The data collection process involved distributing a comprehensive questionnaire throughout Thailand, with the aim of achieving a fair and balanced representation of respondents from six distinct regions: northern, central, eastern, western, north-eastern, and southern. The study included a total of 2100 participants. Twenty hypotheses were formulated to analyze the relationship between the latent constructs. Factor analysis and Structural Equation Modeling were utilized to analyze the data from the questionnaires. The results from SEM found that the model was consistent with the empirical data. The model of the during COVID-19 pandemic had three supported hypotheses, namely H2d, H5d, and H9d, which were the correlation between tourism motivation and perceived severity, self-efficacy, and outcome expectations, respectively. In the post-COVID-19 pandemic period, seven hypotheses, including H1p, H2p, H3p, H4p, H5p, H9p, and H10p, supported the correlation between intention and perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, outcome expectations, and frequency. The support for H10p indicated that stimulated motivation could lead to behavioral changes and increase people’s travel frequency. This study proposes policy recommendations and public relations guidelines to encourage more frequent travel.
Low-Carbon Manufacturing or Not? Equilibrium Decisions for Capital-Constrained News Vendors with Subsidy and Carbon Tax
Authors: Zheng Yanyan , Zhang Jin , Wang Mengyuan , Liu Peng , Shu Tong
Published: July 2023

At a time when low-carbon life has become an important global issue, the decarbonization of manufacturing enterprises cannot be delayed in the face of the government’s green policy and other objective conditions. Under these circumstances, how to arrange the production plan before and after the implication of low-carbon policies is an urgent issue to be settled, especially for the capital-constrained news vendors. To address these problems, this paper firstly builds a stylized supply chain model consisting of two different types of manufacturers (i.e., low-carbon type and traditional type) with capital constraints, then obtains equilibrium production and business strategies resorting to Stackelberg game theory, and lastly conducts an analysis of how the key factors affect manufacturers’ green transition decisions under different scenarios of carbon policy. With the study’s structure, some interesting and important results and managerial insights are derived. For example, but not limited to, it is found that: (i) compared with traditional products, the price fluctuation of low-carbon products is greater than that of traditional products with the increase in consumers’ low-carbon awareness. And consumers have more tolerance for price increases for low-carbon products. (ii) When producing low-carbon products is cost-effective, it is a wise choice to produce more low-carbon products. When producing low-carbon items is costly, producing more low-carbon products is still a dominant strategy until the expenditure difference between low-carbon and traditional ones exceeds a certain threshold. (iii) When the expenditure on low-carbon production is moderate, the manufacturer first prefers the traditional strategy, then the low-carbon one, with an increase in consumers’ low-carbon awareness. When the expenditure on low-carbon production stays at a low or high level, the low-carbon strategy always dominates the traditional one with a certain condition satisfied. This study can enrich the theory of green supply chain management and provide decision support for enterprise managers in the green transition.
Blockchain with Quantum Mayfly Optimization-Based Clustering Scheme for Secure and Smart Transport Systems
Authors: Alamro Hayam , Alqahtani Hamed , Alruwaili Fahad F. , Aljameel Sumayh S. , Rizwanullah Mohammed
Published: July 2023

Blockchain (BC) with a clustering scheme can be used to build secure and smart Vehicular Ad-Hoc Networks (VANETs), which provide improved data integrity, enhanced security, efficient resource allocation, and streamlined processes. This technology has revolutionized the transport industry by enabling safer, more efficient, and transparent transportation networks. Therefore, this paper concentrates on the design of a new Blockchain with a Quantum Mayfly Optimization-based Clustering Scheme for Secure and Smart Transport Systems (BQMFO-CSSTS) technique. The objective of the presented BQMFO-CSSTS technique is to build a secure VANET via a BC-based technology and clustering process. Moreover, the BQMFO-CSSTS technique initially uses a Quantum Mayfly Optimization (QMFO) system with a fitness function for the selection of cluster heads (CHs) and the cluster construction process. In addition, BC technology is used as trust infrastructure to provide trustworthy services to the user and protect the privacy of the CHs and cluster members (CMs). The proposed scheme leverages the decentralized and immutable nature of BC to establish trust and ensure the integrity of cluster formation in VANETs. Finally, the BQMFO-CSSTS technique uses trajectory similarity metrics to protect the integrity of the CMs against attacks. The simulation results of the BQMFO-CSSTS technique are validated using a series of measures. The comprehensive results reported the superior outcomes of the BQMFO-CSSTS method over other recent approaches, with the maximum throughput being 1644.52 kbps. Therefore, integration of BC technology provides a transparent and secure framework through which to manage cluster membership, data sharing, and trust establishment among vehicles.
Assessment of the Hydrophysical and Hydrochemical Characteristics of Lake Burabay (Akmola Region, North Kazakhstan)
Authors: Shulembayeva Kyzzhibek , Rodrigo-Ilarri Javier , Rodrigo-Clavero María-Elena , Khussainov Abilzhan , Kakabayev Anuarbek , Khussainova Razya
Published: July 2023

This paper shows the results of a study on the morphometric, hydrophysical, and hydrochemical indicators of Lake Burabay, North Kazakhstan. The Burabay Protected Area, also known as Burabay National Park or Kokshetau National Park, is a protected natural area located in the north of Kazakhstan. It encompasses a diverse landscape characterized by lakes, forests, and unique rock formations. This analysis includes an eco-toxicological assessment of the hydrochemical composition of waters and benthal deposits by studying the content of metals. The degree of mineralization, ionic composition of water, hydrogen index, pollution index, and water quality class were also determined. Reductions in the area and depth of the lake were identified. The pollution index is 1.5–1.7, which belongs to class 3—moderately polluted. Relatively high concentrations of cadmium, nickel, copper, and arsenic were found in the lake sediments. Therefore, Lake Burabay and its surrounding ecosystem face certain environmental risks and potential water pollution. Although the increase in the number of tourists did not have a significant impact on the water pollution index in Lake Burabay, some of the common threats that impact the area are induced by touristic development, agricultural practices and industrial pollution. Significant efforts should be made to reduce these risks using the environmental indicators as a reference for control environmental quality.
Influence of the Bed Temperature on the Operational Reliability of a Hybrid Constructed Wetland Wastewater Treatment Plant in South-Western Poland—A Case Study
Authors: Jóźwiakowska Karolina , Bugajski Piotr
Published: July 2023

The aim of this study was to assess the influence of atmospheric air temperature on the efficiency and reliability of pollutants removal from wastewater. The studied facility was a hybrid constructed wetland wastewater treatment plant with vertical and horizontal flow serving a single-family building in the village of Krajanów in south-western Poland. The operation of the facility was evaluated on the basis of studies conducted in 2021–2022. The tests included a physico–chemical analysis of wastewater treated mechanically in a settling tank and effluents from constructed wetland beds with the vertical and horizontal flow. The following parameters were determined: BOD5, COD, total suspended solids, total nitrogen, and total phosphorus. No statistically significant effect of air temperature on the analyzed pollutants removal levels was found. The temperature in the soil–plant bed never fell below 0 °C, and so the wastewater flowing through the beds never froze. The discussed facility was characterized by high efficiency and reliability of the tested pollutants removal across the seasons. The mean concentrations of pollutants in treated wastewater did not exceed the limit values specified in the currently binding legal act. It was shown that hybrid constructed wetlands can be successfully used for wastewater treatment in the climatic conditions of southern Poland.
The Functions of Cholera Toxin Subunit B as a Modulator of Silica Nanoparticle Endocytosis
Authors: Susnik Eva , Balog Sandor , Taladriz-Blanco Patricia , Petri-Fink Alke , Rothen-Rutishauser Barbara
Published: July 2023

The gastrointestinal tract is the main target of orally ingested nanoparticles (NPs) and at the same time is exposed to noxious substances, such as bacterial components. We investigated the interaction of 59 nm silica (SiO2) NPs with differentiated Caco-2 intestinal epithelial cells in the presence of cholera toxin subunit B (CTxB) and compared the effects to J774A.1 macrophages. CTxB can affect cellular functions and modulate endocytosis via binding to the monosialoganglioside (GM1) receptor, expressed on both cell lines. After stimulating macrophages with CTxB, we observed notable changes in the membrane structure but not in Caco-2 cells, and no secretion of the pro-inflammatory cytokine tumor necrosis factor-α (TNF-α) was detected. Cells were then exposed to 59 nm SiO2 NPs and CtxB sequentially and simultaneously, resulting in a high NP uptake in J774A.1 cells, but no uptake in Caco-2 cells was detected. Flow cytometry analysis revealed that the exposure of J774A.1 cells to CTxB resulted in a significant reduction in the uptake of SiO2 NPs. In contrast, the uptake of NPs by highly selective Caco-2 cells remained unaffected following CTxB exposure. Based on colocalization studies, CTxB and NPs might enter cells via shared endocytic pathways, followed by their sorting into different intracellular compartments. Our findings provide new insights into CTxB’s function of modulating SiO2 NP uptake in phagocytic but not in differentiated intestine cells.
Mechanistic Understanding of the Antiviral Properties of Pistachios and Zeaxanthin against HSV-1
Authors: Pennisi Rosamaria , Trischitta Paola , Tamburello Maria Pia , Barreca Davide , Mandalari Giuseppina , Sciortino Maria Teresa
Published: July 2023

The search for alternative clinical treatments to fight resistance and find alternative antiviral treatments for the herpes simplex virus (HSV) is of great interest. Plants are rich sources of novel antiviral, pharmacologically active agents that provide several advantages, including reduced side effects, less resistance, low toxicity, and different mechanisms of action. In the present work, the antiviral activity of Californian natural raw (NRRE) and roasted unsalted (RURE) pistachio polyphenols-rich extracts was evaluated against HSV-1 using VERO cells. Two different extraction methods, with or without n-hexane, were used. Results showed that n-hexane-extracted NRRE and RURE exerted an antiviral effect against HSV-1, blocking virus binding on the cell surface, affecting viral DNA synthesis as well as accumulation of ICP0, UL42, and Us11 viral proteins. Additionally, the identification and quantification of phenolic compounds by RP-HPLC-DAD confirmed that extraction with n-hexane exclusively accumulated tocopherols, carotenoids, and xanthophylls. Amongst these, zeaxanthin exhibited strong antiviral activity against HSV-1 (CC50: 16.1 µM, EC50 4.08 µM, SI 3.96), affecting both the viral attachment and penetration and viral DNA synthesis. Zeaxanthin is a dietary carotenoid that accumulates in the retina as a macular pigment. The use of pistachio extracts and derivates should be encouraged for the topical treatment of ocular herpetic infections.