bluuebunny/crossref_metadata_2025 huggingface dataset:
Factors Affecting Travel Behaviour Change towards Active Mobility: A Case Study in a Thai University
Authors: Meesit Ratthaphong , Puntoomjinda Shongwut , Chaturabong Preeda , Sontikul Sumethee , Arunnapa Supattra
Published: July 2023

This study investigates the factors influencing travel behaviour change towards active mobility (AM) in the context of a suburban university in Thailand. The research framework involves developing a qualitative questionnaire for a SWOT analysis. The outcomes of this analysis inform the creation of a quantitative questionnaire called the Stated Preference Survey. This survey collects opinions from 400 randomly selected individuals representing various demographics in the study area. The collected data are then analysed using a binary logistic regression model to explore the relationship between independent variables (such as demographics, travel characteristics, and perceptions of infrastructure and amenities) and the likelihood of individuals adopting AM. The results indicate that the demographic variables, such as gender and income, played a significant role, with males and higher-income individuals showing lower likelihood of adopting AM. The presence of well-designed infrastructure with aesthetic features and rest areas along pedestrian and bicycle paths positively influenced behaviour change. Safety and security measures, including protective measures against motorcycles on pedestrian paths, installing CCTV cameras, and safe crossings, also played a crucial role. However, promotional efforts through media and applications did not significantly contribute to behaviour change. Policymakers and urban planners can use these insights to effectively encourage AM.
A Study of the Interaction between User Psychology and Perceived Value of AI Voice Assistants from a Sustainability Perspective
Authors: Liu Shanshan , Lee Jong-Yoon , Cheon Yongseok , Wang Minglu
Published: July 2023

With the development and innovation of artificial intelligence (AI) technology, users can regulate their social lives and personal emotions through continuous interaction with AI voice assistants or chatbots. Based on the value-based adoption model (VAM), this paper examines the differences between different psychological factors with respect to perceived value factors when using AI voice assistants. This study is of great significance to improving AI voice assistant services and provides an important reference point for deeper understanding of user perception and emotional response to AI voice assistants. The aim of this research is to examine whether the usefulness, enjoyment value, perceived emotional value, and functional value of an AI voice assistant vary according to the user’s level of loneliness, resistance to innovation, and infringement of privacy. An online questionnaire created on the Questionnaire Star platform was used in this paper, and a three-way ANOVA was employed using SPSS 21.0 software. The findings suggest that the interaction effects of psychological factors such as loneliness, innovation resistance, and infringement of privacy differ in terms of perceived usefulness and enjoyment when using AI voice assistants, as well as in terms of perceived emotional and functional value. The results of this study provide a theoretical basis for the application and sustainable development of AI voice assistant technology by companies in different countries and regions. At the same time, this paper provides a valuable reference point for promoting urban economic sustainability in the context of digital technology.
Development of an Algorithm for Textile Waste Arrangement
Authors: Indrie Liliana , Ilieva Julieta , Zlatev Zlatin , Tripa Simona , Sturza Amalia
Published: July 2023

With the constant availability of new designs at extremely low prices, the production and disposal of clothing have increased significantly, leading to the need for the sustainable management of processes. The implementation of established craft practices in modern sustainable mass production requires the development and application of software and hardware computer tools as well as production machinery. Although the management of textile waste for interior design articles is addressed in the scientific literature by various techniques, there is still limited data and strategies based on the use of specific algorithms. Therefore, in this research, an algorithm is proposed, with the help of which textile waste resulting from upholstery production can be reused in the creation of interior decoration parts. The algorithm is implemented in the GNU Octave 6.4 programming environment, which makes it easily redistributable and accessible. The algorithm consists of a total of six stages, offering an option for arranging the textile elements and analyzing their color characteristics. The arrangement is performed with a Voronoi diagram, and the colors are represented by a four-color circle. Moreover, data on waste textile fabrics are presented, as well as their application in the conception of interior design elements. The proposed algorithm allows designers to focus on the visual design rather than compatibility checks and constraints. The present paper provides an algorithm for reusing textile wastes, which come in a variety of shapes and colors and are produced throughout the fabric cutting phase of upholstery manufacturing, in order to identify the most optimal combinations in matching irregular waste shapes and combinations of colors, create a suitable pattern for new interior design items, and contribute to improving the sustainable management of textile waste that is produced in considerable amounts.
Analysis of System Balancing and Wind Power Curtailment Challenges in the Ethiopian Power System under Different Scenarios
Authors: Nefabas Kena Likassa , Mamo Mengesha , Söder Lennart
Published: July 2023

In this paper, an hourly dispatch model was developed to analyze the system balancing and wind power curtailment challenges in the future of the Ethiopian electric power grid system. The developed model was validated using historical data and was used for the analysis of the grid system in 2030 with different scenarios. The model was used to examine the impacts of transmission capacity, regulation reserve requirement, and daily minimum generation of hydropower for irrigation with three cases of wind annual energy share of 14.5%, 17.8%, and 25.2%. Thus, the curtailment was found to be below 0.2%, 1.1%, and 9.8% for each case, respectively. The cost of wind energy increases in proportion to the percentage of curtailment and the increase in transmission line capacity. Reducing the minimum hydropower generation results in smaller wind power curtailment and better generation–consumption balancing.
RNA-Pol II Transcription Elongation Factor FpRtfA Is Required for Virulence and Secondary Metabolism in Fusarium pseudograminearum
Authors: Wu Yuxing , Wang Yajiao , Han Sen , Li Qiusheng , Kong Lingxiao
Published: July 2023

The soil-borne pathogen Fusarium pseudograminearum is capable of causing a highly destructive crown disease in wheat. The purpose of this study was to characterize the biological functions, such as of virulence and secondary metabolites (SMs), of a putative RNA-Pol II transcription elongation factor, FpRtfA, in F. pseudograminearum. The current study revealed that the deletion of FpRtfA reduced radial growth compared to wild type in F. pseudograminearum. In addition, FpRtfA was found important to conidiation and response to metal ions and oxidative stress. More importantly, the virulence to the wheat stem base or head was decreased when FpRtfA was deleted. Using genome-wide gene expression profiling, FpRtfA was found to regulate several processes related to the above phenotype, such as the carbohydrate metabolic process, and the response to oxidative stress and oxidoreductase activity, especially for SMs. Further, we proved that FpRtfA exerts its regulatory effect on the virulence of pathogens by modulating the expression of the PKS gene, but not the generation of DON. In conclusion, FpRtfA has important roles in growth, asexual development, and the response to metal ions and oxidative stress. More importantly, FpRtfA is required for SMs and full virulence in F. pseudograminearum.
Study on Shear Behavior and Mechanism Based on Shear Functional Unit of Loess Microstructure
Authors: Hao Zhitao , Li Xi’an , Gao Rongrong , Yao Wang , Wang Yukun , Zhao Wenqi , Sang Hongbo
Published: July 2023

The structural specificity and hydrological sensitivity of loess have a strong impact on its long-term stability and safety. This topic is being actively researched and focuses on the macromechanical behavior of the shear strength of loess disturbed and its micromechanisms from the perspective of the dry–wet cycle (especially involving soluble salt erosion). In this paper, the correlation between micro-structural shear functional units and macroscopic degradation behavior was established by combining the changes in physicochemical properties of mass loss, surface cracking, strength deterioration, and structural disturbance of the loess with scanning electron microscopy (SEM) microscopic images in different dry–wet cycles and different salt contents. Results revealed that with the increase in dry–wet cycles and salt content, the mass loss of soil deteriorated and the surface crack rate increased. The cohesion of soil showed an overall decreasing trend, which decreased more obviously in the early stage of the dry–wet cycle, followed by a slow decrease, and tended to be constant after nine dry–wet cycles. However, the internal friction angle increased and then decreased during the whole cycle, and its value generally changed little. According to the deterioration and decay of shear strength, it can be concluded that the structural disturbance of loess increased with the increase in dry–wet cycles and salt content. At the same time, further linear quantization fitting of the structural disturbance parameters showed that the structural parameters had a positive correlation with salt content and a power function with dry–wet cycles, where dry–wet cycles seemed to play a dominant role in the loess structural deterioration rather than salt content. The microscopic study demonstrates that the dry–wet cycles and salt content do not directly affect the cohesion and internal friction angle of soil but change the basic shear structural unit of aggregate and then cause an essential impact on c and φ, which in turn have an essential impact on soil strength attenuation. This paper not only helps to elucidate the essence of water–soil–salt structural interactions but also provides theoretical references for sustainable development research in environmental engineering, geological engineering, and other related fields.
The Evolution of Multifunctional Agriculture in Italy
Authors: Cardillo Concetta , Cimino Orlando , De Rosa Marcello , Francescone Martina
Published: July 2023

This study dealt with multifunctional farming, which is meant as a dynamic strategy that is carried out by Italian farms. The path alongside the multifunctional paradigm is carried out through both supply chain and territorial strategies, which deserve more attention. These strategies reinforce sustainable business models characterized by the presence of both deepening and broadening strategies. The first ones are centered around product differentiation and valorization through geographical indications, organic farming, etc. Broadening strategies are implemented through new on-farm activities, such as agritourism, and other gainful activities carried out at the farm level. Set against this background, the article discusses the evolution of farms according to the Farm Accountancy Data Network (FADN) database by putting forward an empirical analysis, which considered the evolution of farm typologies oriented toward multifunctionality in the last decade. The analysis underlined the positive dynamics and the evolution of farms adhering to the multifunctional paradigm. Moreover, as evidenced in the econometric analysis, the adoption of multifunctional farming activities provided a sound contribution to income formation. This addressed some policy issues that were identified at the beginning of the new programming period for rural development of the EU and their resolution aims to reinforce the virtuous trajectory toward multifunctional farming.
Collaboration between Oil Development and Water/Power Consumption in High-Water-Cut Oilfields
Authors: Jia Deli , Zhang Jiqun , Sun Yufei , Wang Suling , Gao Sheng , Qiao Meixia , Li Yanchun , Qu Ruyi
Published: July 2023

Waterflooding is the main development technique used in the vast majority of oilfields in the world. However, as the waterflood oilfields enter the stages with (ultra-)high water cut, the water/power consumption per ton of oil remains unabatedly high. This paper presents a systematic analysis of the development stages and strategies of some typical waterflood oilfields in the world and proposes the necessity to establish a mode and technical system of collaboration between oil development and water/power consumption in mature oilfields with (ultra-)high water cut. Then, taking a pilot test area of an ultra-high-water-cut oilfield in northeastern China as an example, this paper investigates its development mode and water/power consumption; optimizes the technical strategies from the aspects of fine reservoir analysis, artificial lift system and surface gathering system; and predicts the application results. It is found that the optimizations of fine reservoir analysis and development plans effectively reduce the water consumption per ton of oil and have a certain but not remarkable contribution to the power consumption per ton of oil. Moreover, the optimizations of the artificial lift system and surface gathering system significantly reduce the power consumption per ton of oil. Under conditions of low production and low efficiency, the optimization of the artificial lift system greatly improves the energy-saving effect, which will be a focus of future research. Finally, this paper recommends measures for collaboration between oil development and water/power consumption in high-water-cut oilfields.
Short-Term PM2.5 Concentration Changes Prediction: A Comparison of Meteorological and Historical Data
Authors: Kang Junfeng , Zou Xinyi , Tan Jianlin , Li Jun , Karimian Hamed
Published: July 2023

Machine learning is being extensively employed in the prediction of PM2.5 concentrations. This study aims to compare the prediction accuracy of machine learning models for short-term PM2.5 concentration changes and to find a universal and robust model for both hourly and daily time scales. Five commonly used machine learning models were constructed, along with a stacking model consisting of Multivariable Linear Regression (MLR) as the meta-learner and the ensemble of Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) as the base learner models. The meteorological datasets and historical PM2.5 concentration data with meteorological datasets were preprocessed and used to evaluate the model’s accuracy and stability across different time scales, including hourly and daily, using the coefficient of determination (R2), Root-Mean-Square Error (RMSE), and Mean Absolute Error (MAE). The results show that historical PM2.5 concentration data are crucial for the prediction precision of the machine learning models. Specifically, on the meteorological datasets, the stacking model, XGboost, and RF had better performance for hourly prediction, and the stacking model, XGboost and LightGBM had better performance for daily prediction. On the historical PM2.5 concentration data with meteorological datasets, the stacking model, LightGBM, and XGboost had better performance for hourly and daily datasets. Consequently, the stacking model outperformed individual models, with the XGBoost model being the best individual model to predict the PM2.5 concentration based on meteorological data, and the LightGBM model being the best individual model to predict the PM2.5 concentration using historical PM2.5 data with meteorological datasets.
The Role of Citizen Science in Promoting Ocean and Water Literacy in School Communities: The ProBleu Methodology
Authors: Ceccaroni Luigi , Woods Sasha M. , Butkevičienė Eglė , Parkinson Stephen , Sprinks James , Costa Pedro , Simis Stefan G. H. , Lessin Gennadi , Liñán Sonia , Companys Berta , Bonfill Elisabet , Piera Jaume
Published: July 2023

Human activities continue to degrade oceanic, coastal and inland waters. The generational change in the role of society in actively looking after the health of water resources can be achieved through the expansion of ocean and water literacy in schools. The Network of European Blue Schools established under the EU4Ocean Coalition for Ocean Literacy has improved ocean and water literacy; however, this Network needs to grow and be supported. Here, we present ProBleu, a recently funded EU project that will expand and support the Network, partly through the use of citizen science. The core of the proposed methodology is facilitating school activities related to ocean and water literacy through funding calls to sustain and enrich current school activities, and kick-start and support new activities. The outcomes of the project are anticipated to have widespread and long-term impacts across society, and oceanic, coastal and inland water environments.
Correlation of Two Biodegradability Indices of PLA-Based Polymers under Thermophilic Aerobic Laboratory Conditions
Authors: Melitou Dimitra , Gerassimidou Spyridoula , Averopoulou Athanassia , Komilis Dimitrios
Published: July 2023

The biodegradation of bioplastics is a topic of interest worldwide. This work aims to measure the biodegradability of five polylactic acid (PLA)-based bioplastics under aerobic, thermophilic laboratory conditions and correlate their weight loss with their CO2 generation over a 3-month period, as both are considered indexes of biodegradation. The experimental design was based on the simulation of composting conditions by placing the bioplastic samples mixed with compost in sealed glass vessels that were regularly opened. The results showed significant variability in biodegradation, as dry weight losses ranged from 15.1–99.7%, while CO2 generation ranged from 9.2–14.9 g C–CO2/kg dry mixture (bioplastic + inoculum) depending on the sample. Moreover, no significant correlation between the weight losses and the gross CO2 production was calculated (p = 0.656), indicating the importance of carefully selecting the methods to assess biodegradation potential. This lack of correlation also reveals that different pathways are likely involved during the biodegradation of bioplastics and that the weight loss alone cannot indicate the conversion of solid C to CO2. This work proposes the need to develop an optimal degradation index for bioplastics that would provide a better understanding of their biodegradability in composting reactors. This index should combine dry weight loss and CO2 generation to assess the biodegradation of bioplastics with high confidence.
Enhancing Shoppers’ Experiences and Building Mall Loyalty: The Role of Octomodal Mental Imagery (OMI) and Management Dimension-Evidence from the Yangtze River Delta Region of China
Authors: Zhu Zhenxing , Chung Wonjun
Published: July 2023

This study investigated the impact of Octomodal Mental Imagery (OMI) and management dimensions on shoppers’ experiences and mall loyalty. The study was collected through “Questionnaire Star,” and 358 valid data points were obtained. The data were analyzed using SPSS27 and AMOS28. The results showed that sensory attributes such as visual, tactile, gustatory, and olfactory attributes positively influenced shoppers’ experiences in OMI, while the auditory attribute had no significant effect. Spatial, a structural attribute of OMI, positively influenced shoppers’ experiences, whereas autonomy and kinesthetics did not have a considerable effect. Tenant mix and entertainment positively impacted shoppers’ experiences in management, while accessibility had no significant effect. The study also found that shoppers’ experiences positively impacted mall loyalty, while hedonistic motivation had a more substantial effect than utilitarian motivation. This study is the first to examine the impact of OMI on shoppers’ experiences. It fills a gap in the literature on this relationship. It also examines the combined impact of management dimensions (accessibility, tenant mix, and entertainment) on the overall shopper’s experience, filling a gap in the Chinese shopping mall literature and extending the generalizability of the theory. The study further explores the relationship between shoppers’ experiences and mall loyalty and the moderating effect of incentive orientation. The results of this study have critical implications for mall managers. Strengthening the mental image and management dimensions of the shopping mall will enhance shoppers’ experiences and build loyalty, allowing brick-and-mortar malls to remain competitive and sustainable in today’s highly competitive and popular e-commerce environment.
Understanding Travel Mode Choice Behavior: Influencing Factors Analysis and Prediction with Machine Learning Method
Authors: Zhang Hui , Zhang Li , Liu Yanjun , Zhang Lele
Published: July 2023

Building a multimode transportation system could effectively reduce traffic congestion and improve travel quality. In many cities, use of public transport and green travel modes is encouraged in order to reduce the emission of greenhouse gas. With the development of the economy and society, travelers’ behaviors become complex. Analyzing the travel mode choices of urban residents is conducive to constructing an effective multimode transportation system. In this paper, we propose a statistical analysis framework to study travelers’ behavior with a large amount of survey data. Then, a stacking machine learning method considering travelers’ behavior is introduced. The results show that electric bikes play a dominant role in Jinan city and age is an important factor impacting travel mode choice. Travelers’ income could impact travel mode choice and rich people prefer to use private cars. Private cars and electric bikes are two main travel modes for commuting, accounting for 30% and 35%, respectively. Moreover, the proposed stacking method achieved 0.83 accuracy, outperforming the traditional multinomial logit (MNL) mode and nine other machine learning methods.
Developing Iron Ore Pellets Using Novel Binders for H2-Based Direct Reduction
Authors: Parathodiel Harikrishnan , Mousa Elsayed , Ahmed Hesham , Elsadek Mohamed , Forsberg Kerstin , Andersson Charlotte
Published: July 2023

The transformation from traditional iron- and steelmaking technologies to green H2-based new technologies will require an improvement in the quality and purity of iron ore burden materials. Iron ore pellets are essential inputs for producing direct reduced iron (DRI), but the conventional binders, used in iron ore pelletizing, introduce gangue oxides to the DRI and consequently increase the slag generation and energy consumption in the steelmaking unit. Partial and/or full replacement of the traditional binders with novel organic binders would significantly contribute to improving the process efficiency, particularly in the next-generation H2-based direct reduction technology. This study illustrates the feasibility of pelletizing magnetite iron ore concentrate using four organic binders: KemPel, Alcotac CS, Alcotac FE16, and CMC, in comparison to bentonite as a reference. The study explores the influence of binder type, binder dosage, and moisture content on the characteristics and properties of the pellets. The efficiency of binders was characterized by the moisture content, drop number test, cold compression strength, and H2 reduction of pellets. For dry pellets, CMS was superior among other binders including bentonite in developing dry strength. After firing, the pellets produced by the partial replacement of bentonite with 0.1 wt.% KemPel demonstrate a performance nearly identical to the reference pellets. While the complete replacement of bentonite with organic binder shows a lower performance of fired pellets compared to the reference, it may still be suitable for use in DR shaft furnaces. The cold-bonded pellets demonstrate a superior reduction rate compared to fired pellets.
Investigating the Spatial-Temporal Variation of Pre-Trip Searching in an Urban Agglomeration
Authors: Zhang Jianxin , Yan Yuting , Zhang Jinyue , Liu Peixue , Ma Li
Published: July 2023

Search engines have been the primary tool for online information search before traveling. Timely detection and the control of peak tourist flows in scenic areas prevent safety hazards and the overconsumption of tourism resources due to excessive tourist clustering. This study focuses on the spatial-temporal interactions between the pre-trip stage and the after-arrival stage to investigate online information search behavior. Big data obtained from mobile roaming and search engines provide precise data on daytime and city scales, which enabled this paper to examine the relationship between daily tourist arrivals and their pre-trip searching from 40 cities within the Yangtze River Delta urban agglomeration. This study had several original results. First, tourists generally search for tourist information 2–8 days before arriving at destinations, while tourist volume and SVI from source cities show distance attenuation. Second, SVI is a precursor to changes in tourist volume. The precursory time rises with the increase of traffic time spatially. Third, we validated a VAR model and improved its accuracy by constructing it based on the spatial-temporal differentiation of search features. These findings would enhance the management and preservation of tourism resources and promote the sustainable development of tourism destinations.
The Harmonious Relationship between Energy Utilization Efficiency and Industrial Structure Development under Carbon Emission Constraints: Measurement, Quantification, and Identification
Authors: Han Ping , Zhou Ziyu
Published: July 2023

Addressing the challenge of attaining a harmonious balance between energy utilization efficiency and the level of industrial structure development is crucial for promoting regional sustainable development. Aiming at the goal of carbon neutrality, a three-stage method to analyze the relationship between energy utilization and industrial structure development is proposed. The multidimensional input–output index system was augmented with a carbon emission constraint. Additionally, two classical data envelopment analysis models were integrated to establish a dynamic measurement model for energy utilization efficiency, ensuring comparability among all decision-making units. From two perspectives of industrial structure, rational degree and advanced degree, the industrial structure development index was proposed to quantitatively characterize the level of regional industrial structure development. Drawing upon the Tapio decoupling theory, an elaborate model for identifying harmonious relationships was constructed to refine the recognition of the harmonious state between energy utilization efficiency and industrial structural development. A city-scale case study was conducted in Heilongjiang Province, a typical energy province in Northern China. The results revealed that: (a) energy utilization efficiency in various cities has exhibited a consistent upward trend, with the average efficiency rising from 0.54 in 2010 to 0.88 in 2020. Core cities like Daqing and Harbin stand out in energy utilization, and the disparity in energy utilization levels between different cities is progressively diminishing; (b) the overall level of industrial structural development has shown a weak downward trend. Harbin has the best industrial structure development level, with a quantitative index higher than 0.8. For some cities with relatively backward industrial structures, it is necessary to clarify new industrial development positioning and promote deep optimization of industrial structures; and (c) the harmonious relationship between energy utilization efficiency and industrial structural development demonstrates stage characteristics, indicating an overall negative decoupling relationship with limited dynamic coordination. These distinct findings will assist in identifying potential solutions for achieving high-quality development in traditional industrial cities under carbon emission constraints.
Numerical Study on Wave Dissipation Performance of OWC-Perforated Floating Breakwater under Irregular Waves
Authors: Zheng Yanna , Li Jiafan , Mu Yingna , Zhang Yu , Huang Siyao , Shao Xiran
Published: July 2023

This paper utilizes ANSYS-AQWA hydrodynamic simulation analysis software (2022 R2) to investigate the wave dissipation performance of an Oscillating Water Column (OWC) perforated floating breakwater under irregular wave conditions. The study examines the effect of spacing, width of the OWC opening, water depth, incident wave angle, and significant wave height on the wave dissipation performance of the floating breakwater. The results indicate that the wave dissipation performance of the OWC-perforated floating breakwater surpasses that of similar structures. The transmission coefficient is significantly influenced by spacing and water depth when subjected to irregular waves. The width of the OWC opening also affects the wave dissipation to some extent, with wider openings demonstrating improved performance in the case of long-period waves. The incident wave angle of 0 degrees yields enhanced wave dissipation performance. Although the meaningful wave height has minimal impact on wave dissipation, it increases proportionally with the rise in meaningful wave height. This study offers valuable insights for the design and implementation of floating breakwaters and holds significant practical implications for the research on integrated devices combining floating breakwaters and wave power generation.
Development of Artificial Intelligence Based Safety Performance Measures for Urban Roundabouts
Authors: Alanazi Fayez , Umar Ibrahim Khalil , Haruna Sadi Ibrahim , El-Kady Mahmoud , Azam Abdelhalim
Published: July 2023

A reliable model for predicting crash frequency at roundabouts is an essential tool for evaluating the safety measures of a roundabout. This study developed a hybrid PSO-ANN model by optimizing the modeling parameters of the classical artificial neural network (ANN) model with the particle swarm optimization algorithm (PSO). The performance accuracy of the models was evaluated using the mean absolute error (MAE), root mean square error (RMSE), and determination coefficients (DC). The PSO-ANN model predicted the crash frequency with very good accuracy at the testing stage (DC = 0.7935). The hybrid model could improve the performance of the classical ANN model by up to 23.3% in the training stage and 16.9% in the testing stage. In addition to the statistical measures, graphical approaches (scatter and violin plots) were also used for evaluating the models’ accuracy. Both statistical and graphical evaluation techniques prove the reliability and accuracy of the proposed hybrid model in predicting the crash frequency at roundabouts.
The Healthy Workplaces Ecosystems and Professionals’ Stress Management during the COVID-19 Pandemic
Authors: Gaspar Tânia , Salado Vanesa , Machado Maria do Céu , Guedes Fábio Botelho , Correia Manuela Faia , Matos Margarida Gaspar
Published: July 2023

The main objective of this paper is to understand and characterize the healthy work environment of organizations during the COVID-19 pandemic. The study was carried out in 2021 including organizations from different sectors at the national level and involved 460 participants, 50.3% of which were female. The workers’ ages ranged between 18 and 67 years, with a mean of 44 years and a standard deviation of 11.36. The Healthy Workplaces Ecosystems Tool was used. Data was collected online from professionals in the organizations who agreed to participate in the study. Our results show that organizational culture has a strong relationship with the other components of a healthy work environment. Values, policies, and practices related to leadership engagement and professional involvement are related to the psychosocial work environment, the physical work environment, the social responsibility, heath, and stress management resources. The results confirm that an organizational culture that values the well-being and health of the organization’s professionals has a positive relationship with the psychosocial environment, the physical environment, and the relationship with the community and has more resources for professionals’ health. It was also found that an organizational culture mediated by the psychosocial environment is associated with more effective stress management. Management can use this model and this tool for systemic assessment of healthy workplace ecosystems within organizations, thus contributing to continuous monitoring improvements, helping to face the challenges proposed by the Sustainable Development Goals of the United Nations’ 2030 Agenda, namely the SDG3, Good Health and Wellbeing and Decent Work; SDG5, Gender Equality; and SDG 10, Sustainable cities and communities.
Sustainability Study of a New Solid-State Aluminum Chips Recycling Process: A Life Cycle Assessment Approach
Authors: El Mehtedi Mohamad , Buonadonna Pasquale , Carta Mauro , El Mohtadi Rayane , Mele Alessandro , Morea Donato
Published: July 2023

Nowadays, reducing greenhouse gas emissions in all human activities has become crucial. This article presents a life cycle assessment (LCA) investigation conducted to evaluate the environmental benefits of a newly developed solid-state recycling process for aluminum chips, involving two steps: direct rolling and accumulative roll bonding. A comparison was made between this process and two current industrial methods of recycling aluminum scraps to obtain wrought products, which involve melting, casting, and subsequent rolling. The LCA analysis considered a scenario where 50% of the total electric requirement was met by photovoltaic energy. The results of the study indicate that in all examined impact categories, direct rolling has a lower environmental footprint compared to both traditional recycling and twin-roll cast technology. These results suggest that this new solid-state recycling procedure has significant potential to replace environmentally harmful melting processes.
Structural Equation Modeling of the Marine Ecological System in Nanwan Bay Using SPSS Amos
Authors: Huang Jung-Fu , Chen Chen-Tung Arthur , Chen Meng-Hsien , Huang Shih-Lun , Hsu Pi-Yu
Published: July 2023

To ensure the sustainability of the marine environment, it is crucial to understand the intricate relationship between environmental factors and marine biota. Human activities have been recognized as significant contributors to profound changes in marine ecology. However, these observable alterations often represent a cumulative effect that intertwines with less apparent natural influences. This research delved into the relationships between environmental factors and marine life in the waters adjacent to Nanwan Bay, Kenting, Taiwan. Specifically, it examined the linear relationships and the degree of changes between environmental factors and marine life. To achieve these objectives, factor analysis was employed to uncover potential latent variables that could impact marine organisms, with these variables named based on previous studies and related literature. The findings led to the development of a structural equation model (SEM) to represent the marine ecology of Nanwan Bay. The results accentuated the significant influence of primary productivity and nutrient levels on the assemblage of marine life. The application of SEM methodology sheds more light on the degree of impact natural and anthropogenic interference have on marine ecosystems.
From Wastewater Treatment Plants to the Oceans: A Review on Synthetic Chemical Surfactants (SCSs) and Perspectives on Marine-Safe Biosurfactants
Authors: Fung Karen C. L. , Dornelles Henrique S. , Varesche Maria B. A. , Gutierrez Tony
Published: July 2023

Synthetic chemical surfactants (SCSs) are a versatile group of amphiphilic chemical compounds synthesized from fossil fuel precursors which have found use in various industrial applications. Their global usage is estimated to be over 15 million tons annually, which has resulted in unabated environmental damage and potential toxicological effects to humans and other organisms. Current societal challenges to ensure environmental protection and reduce reliance on finite resources have led to an increased demand for sustainable and environmentally friendly alternatives, such as biosurfactants, to replace these toxic pollutants. Biosurfactants are biodegradable, non-toxic, and generally environmentally compatible amphiphilic compounds. Although there is enormous potential for microbial biosurfactants to replace SCSs, the key challenge limiting their commercialization relates to their low yields and substantial cost for production compared to that for the SCSs. In this review, we discuss the release of SCSs, with wastewater treatment plants (WWTPs) as the major point source of their release into the ocean, and we then delve into the consequences of these pollutants on marine organisms and humans. We then explore microbial biosurfactants as a replacement for SCSs, with a focus on rhamnolipids, and end with some perspectives on current and future work for commercializing microbial biosurfactants.
A Feature Fusion Human Ear Recognition Method Based on Channel Features and Dynamic Convolution
Authors: Xu Xuebin , Liu Yibiao , Liu Chenguang , Lu Longbin
Published: July 2023

Ear images are easy to capture, and ear features are relatively stable and can be used for identification. The ear images are all asymmetric, and the asymmetry of the ear images collected in the unconstrained environment will be more pronounced, increasing the recognition difficulty. Most recognition methods based on hand-crafted features perform poorly in terms of recognition performance in the face of ear databases that vary significantly in terms of illumination, angle, occlusion, and background. This paper proposes a feature fusion human ear recognition method based on channel features and dynamic convolution (CFDCNet). Based on the DenseNet-121 model, the ear features are first extracted adaptively by dynamic convolution (DY_Conv), which makes the ear features of the same class of samples more aggregated and different types of samples more dispersed, enhancing the robustness of the ear feature representation. Then, by introducing an efficient channel attention mechanism (ECA), the weights of important ear features are increased and invalid features are suppressed. Finally, we use the Max pooling operation to reduce the number of parameters and computations, retain the main ear features, and improve the model’s generalization ability. We performed simulations on the AMI and AWE human ear datasets, achieving 99.70% and 72.70% of Rank-1 (R1) recognition accuracy, respectively. The recognition performance of this method is significantly better than that of the DenseNet-121 model and most existing human ear recognition methods.
Symmetric Perfect and Symmetric Semiperfect Colorings of Groups
Authors: Santos Rovin B. , Valdez Lilibeth D. , Walo Ma. Lailani B.
Published: July 2023

Let G be a group. A k-coloring of G is a surjection λ:G→{1,2,…,k}. Equivalently, a k-coloring λ of G is a partition P={P1,P2,…,Pk} of G into k subsets. If gP=P for all g in G, we say that λ is perfect. If hP=P only for all h∈H≤G such that [G:H]=2, then λ is semiperfect. If there is an element g∈G such that λ(x)=λ(gx−1g) for all x∈G, then λ is said to be symmetric. In this research, we relate the notion of symmetric colorings with perfect and semiperfect colorings. Specifically, we identify which perfect and semiperfect colorings are symmetric in relation to the subgroups of G that contain the squares of elements in G, in H, and in G∖H. We also show examples of colored planar patterns that represent symmetric perfect and symmetric semiperfect colorings of some groups.
Derivation of Optimal Operation Factors of Anaerobic Digesters through Artificial Neural Network Technology
Authors: Bao Yumeng , Koutavarapu Ravindranadh , Lee Tae-Gwan
Published: July 2023

The anaerobic digestion of sewage sludge in South Korean wastewater treatment plants is affected by seasonal factors and other influences, resulting in lower digestion efficiency and gas production, which cannot reach optimal yields. The aim of this study was to improve the digestion efficiency and gas production of sludge anaerobic digestion in a wastewater treatment plant (WWTP) by using data mining techniques to adjust operational parameters. Through experimental data obtained from the WWTP in Daegu City, South Korea, an artificial neural network (ANN) technology was used to adjust the range of the organic loading rate (OLR) and hydraulic retention rate (HRT) to improve the efficiency and methane gas production from anaerobic sludge digestion. Data sources were normalized, and data analysis including Pearson correlation analysis, multiple regression analysis and an artificial neural network for optimal results. The results of the study showed a predicted 0.5% increase in digestion efficiency and a 1.3% increase in gas production at organic loads of 1.26–1.46 kg/m3 day and an HRT of 26–30 days. This shows that the ANN model that we established is feasible and can be used to improve the efficiency and gas production of sludge anaerobic digestion.
Impacts of Indoor Dust Exposure on Human Colonic Cell Viability, Cytotoxicity and Apoptosis
Authors: Abdulrahman Noura , Honda Trenton J. , Ali Ayat , Abdulrahman Nabras , Vrinceanu Daniel , Shishodia Shishir
Published: July 2023

Introduction: Environmental exposure to indoor dust is known to be associated with myriad health conditions, especially among children. Established routes of exposure include inhalation and non-dietary ingestion, which result in the direct exposure of gastrointestinal epithelia to indoor dust. Despite this, little prior research is available on the impacts of indoor dust on the health of human gastrointestinal tissue. Methods: Cultured human colonic (CCD841) cells were exposed for 24 h to standard trace metal dust (TMD) and organic contaminant dust (OD) samples at the following concentrations: 0, 10, 25, 50, 75, 100, 250, and 500 µg/mL. Cell viability was assessed using an MTT assay and protease analysis (glycyl-phenylalanyl-aminofluorocoumarin (GF-AFC)); cytotoxicity was assessed with a lactate dehydrogenase release assay, and apoptosis was assessed using a Caspase-Glo 3/7 activation assay. Results: TMD and OD decreased cellular metabolic and protease activity and increased apoptosis and biomarkers of cell membrane damage (LDH) in CCD841 human colonic epithelial cells. Patterns appeared to be, in general, dose-dependent, with the highest TMD and OD exposures associated with the largest increases in apoptosis and LDH, as well as with the largest decrements in metabolic and protease activities. Conclusions: TMD and OD exposure were associated with markers of reduced viability and increased cytotoxicity and apoptosis in human colonic cells. These findings add important information to the understanding of the physiologic effects of indoor dust exposure on human health. The doses used in our study represent a range of potential exposure levels, and the effects observed at the higher doses may not necessarily occur under typical exposure conditions. The effects of long-term, low-dose exposure to indoor dust are still not fully understood and warrant further investigation. Future research should explore these physiological mechanisms to further our understanding and inform public health interventions.
Aflatoxin B1 Exacerbates Genomic Instability and Apoptosis in the BTBR Autism Mouse Model via Dysregulating DNA Repair Pathway
Authors: Alshamrani Ali A. , Alwetaid Mohammad Y. , Al-Hamamah Mohammed A. , Attia Mohamed S. M. , Ahmad Sheikh F. , Algonaiah Majed A. , Nadeem Ahmed , Ansari Mushtaq A. , Bakheet Saleh A. , Attia Sabry M.
Published: July 2023

The pathophysiology of autism is influenced by a combination of environmental and genetic factors. Furthermore, individuals with autism appear to be at a higher risk of developing cancer. However, this is not fully understood. Aflatoxin B1 (AFB1) is a potent food pollutant carcinogen. The effects of AFB1 on genomic instability in autism have not yet been investigated. Hence, we have aimed to investigate whether repeated exposure to AFB1 causes alterations in genomic stability, a hallmark of cancer and apoptosis in the BTBR autism mouse model. The data revealed increased micronuclei generation, oxidative DNA strand breaks, and apoptosis in BTBR animals exposed to AFB1 when compared to unexposed animals. Lipid peroxidation in BTBR mice increased with a reduction in glutathione following AFB1 exposure, demonstrating an exacerbated redox imbalance. Furthermore, the expressions of some of DNA damage/repair- and apoptosis-related genes were also significantly dysregulated. Increases in the redox disturbance and dysregulation in the DNA damage/repair pathway are thus important determinants of susceptibility to AFB1-exacerbated genomic instability and apoptosis in BTBR mice. This investigation shows that AFB1-related genomic instability can accelerate the risk of cancer development. Moreover, approaches that ameliorate the redox balance and DNA damage/repair dysregulation may mitigate AFB1-caused genomic instability.
Combination of Zearalenone and Deoxynivalenol Induces Apoptosis by Mitochondrial Pathway in Piglet Sertoli Cells: Role of Endoplasmic Reticulum Stress
Authors: Hai Sirao , Chen Jiawen , Ma Li , Wang Chenlong , Chen Chuangjiang , Rahman Sajid Ur , Zhao Chang , Feng Shibin , Wu Jinjie , Wang Xichun
Published: July 2023

Zearalenone (ZEA) and deoxynivalenol (DON) are widely found in various feeds, which harms livestock’s reproductive health. Both mitochondria and endoplasmic reticulum (ER) can regulate cell apoptosis. This study aimed to explore the regulatory mechanism of endoplasmic reticulum stress (ERS) on ZEA- combined with DON-induced mitochondrial pathway apoptosis in piglet Sertoli cells (SCs). The results showed that ZEA + DON damaged the ultrastructure of the cells, induced apoptosis, decreased mitochondrial membrane potential, promoted the expression of cytochrome c (CytC), and decreased the cell survival rate. Furthermore, ZEA + DON increased the relative mRNA and protein expression of Bid, Caspase-3, Drp1, and P53, while that of Bcl-2 and Mfn2 declined. ZEA + DON was added after pretreatment with 4-phenylbutyric acid (4-PBA). The results showed that 4-PBA could alleviate the toxicity of ZEA + DON toward SCs. Compared with the ZEA + DON group, 4-PBA improved the cell survival rate, decreased the apoptosis rate, inhibited CytC expression, and increased mitochondrial membrane potential, and the damage to the cell ultrastructure was alleviated. Moreover, after pretreatment with 4-PBA, the relative mRNA and protein expression of Bid, Caspase-3, Drp1, and P53 were downregulated, while the relative mRNA and protein expression of Bcl-2 and Mfn2 were upregulated. It can be concluded that ERS plays an important part in the apoptosis of SCs co-infected with ZEA-DON through the mitochondrial apoptosis pathway, and intervention in this process can provide a new way to alleviate the reproductive toxicity of mycotoxins.