bluuebunny/crossref_metadata_2025 huggingface dataset:
Remaining Useful Life Prediction Based on Deep Learning: A Survey
Authors: Wu Fuhui , Wu Qingbo , Tan Yusong , Xu Xinghua
Published: May 2024

Remaining useful life (RUL) is a metric of health state for essential equipment. It plays a significant role in health management. However, RUL is often random and unknown. One type of physics-based method builds a mathematical model for RUL using prior principles, but this is a tough task in real-world applications. Another type of method estimates RUL from available information through condition and health monitoring; this is known as the data-driven method. Traditional data-driven methods require significant human effort in designing health features to represent performance degradation, yet the prediction accuracy is limited. With breakthroughs in various application scenarios in recent years, deep learning techniques provide new insights into this problem. Over the past few years, deep-learning-based RUL prediction has attracted increasing attention from the academic community. Therefore, it is necessary to conduct a survey on deep-learning-based RUL prediction. To ensure a comprehensive survey, the literature is reviewed from three dimensions. Firstly, a unified framework is proposed for deep-learning-based RUL prediction and the models and approaches in the literature are reviewed under this framework. Secondly, detailed estimation processes are compared from the perspective of different deep learning models. Thirdly, the literature is examined from the perspective of specific problems, such as scenarios where the collected data consist of limited labeled data. Finally, the main challenges and future directions are summarized.
Pixel-Level Recognition of Trace Mycotoxins in Red Ginseng Based on Hyperspectral Imaging Combined with 1DCNN-Residual-BiLSTM-Attention Model
Authors: Liu Biao , Zhang Hongxu , Zhu Jieqiang , Chen Yuan , Pan Yixia , Gong Xingchu , Yan Jizhong , Zhang Hui
Published: May 2024

Red ginseng is widely used in food and pharmaceuticals due to its significant nutritional value. However, during the processing and storage of red ginseng, it is susceptible to grow mold and produce mycotoxins, generating security issues. This study proposes a novel approach using hyperspectral imaging technology and a 1D-convolutional neural network-residual-bidirectional-long short-term memory attention mechanism (1DCNN-ResBiLSTM-Attention) for pixel-level mycotoxin recognition in red ginseng. The “Red Ginseng-Mycotoxin” (R-M) dataset is established, and optimal parameters for 1D-CNN, residual bidirectional long short-term memory (ResBiLSTM), and 1DCNN-ResBiLSTM-Attention models are determined. The models achieved testing accuracies of 98.75%, 99.03%, and 99.17%, respectively. To simulate real detection scenarios with potential interfering impurities during the sampling process, a “Red Ginseng-Mycotoxin-Interfering Impurities” (R-M-I) dataset was created. The testing accuracy of the 1DCNN-ResBiLSTM-Attention model reached 96.39%, and it successfully predicted pixel-wise classification for other unknown samples. This study introduces a novel method for real-time mycotoxin monitoring in traditional Chinese medicine, with important implications for the on-site quality control of herbal materials.
Enhancing Maritime Cybersecurity through Operational Technology Sensor Data Fusion: A Comprehensive Survey and Analysis
Authors: Potamos Georgios , Stavrou Eliana , Stavrou Stavros
Published: May 2024

Cybersecurity is becoming an increasingly important aspect in ensuring maritime data protection and operational continuity. Ships, ports, surveillance and navigation systems, industrial technology, cargo, and logistics systems all contribute to a complex maritime environment with a significant cyberattack surface. To that aim, a wide range of cyberattacks in the maritime domain are possible, with the potential to infect vulnerable information and communication systems, compromising safety and security. The use of navigation and surveillance systems, which are considered as part of the maritime OT sensors, can improve maritime cyber situational awareness. This survey critically investigates whether the fusion of OT data, which are used to provide maritime situational awareness, may also improve the ability to detect cyberincidents in real time or near-real time. It includes a thorough analysis of the relevant literature, emphasizing RF but also other sensors, and data fusion approaches that can help improve maritime cybersecurity.
Insights into Women’s Occupational Health and Safety: A Decade in Review of Primary Data Studies
Authors: Bolghanabadi Somayeh , Haghighi Aida , Jahangiri Mehdi
Published: May 2024

Women play integral roles across various sectors, including mining. Moreover, they often form a majority in certain sectors, such as healthcare and education. Biological (sex) and social (gender) differences can influence how hazards are assessed and controlled for women at work. Therefore, because of the importance of women’s occupational health and safety (OHS), this study reviews and analyzes OHS-related research studies to explore (i) the attention given to women’s OHS; (ii) the specific occupations studied; and (iii) the primary OHS issues and challenges faced by women. Following PRISMA guidelines, the study examined articles from 2010–2021, selecting 62 that utilized primary data, with all or part of their participants being female. The results indicate that the included studies examined women’s OHS in specific occupations. These include healthcare workers, farm and forestry workers, office staff, teachers, firefighters, police officers, nail technicians, workers in the clothing industry, and general industrial workers. The trend of publishing articles on women’s OHS has been growing, with most studies focusing on healthcare and agriculture. The USA and South Korea are leading in publications in the field of women’s OHS, while the USA, Australia, and the Netherlands have the highest collaboration rates. Key findings reveal that the most common OHS issues faced by women in various occupations include stress, fatigue, musculoskeletal disorders and pain, sleep disorders, long working hours, depression and anxiety, workplace violence, and allergies and skin problems. Many of these issues are related to mental health. Specific issues based on the nature of the work vary; for example, teachers experience voice disorders, while farmers face digestive problems. This study contributes theoretically by enhancing understanding of women’s OHS, serving as a foundation for further research, and providing practical guidance for employers and policymakers seeking to implement effective strategies for guaranteeing women’s OHS across sectors.
Examining Risky Riding Behaviors: Insights from a Questionnaire Survey with Middle-Aged and Older Motorcyclists in Thailand
Authors: Sunmud Sayam , Arreeras Tosporn , Phonsitthangkun Suchada , Prommakhot Sirin , Sititvangkul Krit
Published: May 2024

This research endeavors to achieve three primary objectives. Firstly, it seeks to develop a measurement model capable of assessing the motorcycle riding behavior of middle-aged individuals in Thailand. The construction of this model integrates the motorcycle rider behavior questionnaire (MRBQ) with statistical and descriptive analyses. Secondly, the research examines the accuracy of the measurement model using a factor analysis approach, comprising both exploratory and confirmatory factor analyses. Lastly, the study aims to furnish the people of Thailand with a set of guidelines for self-assessment of their motorcycle riding habits. The examination involves 399 middle-aged motorcycle riders aged 35 years or older, a significant majority of whom (81%) possess the requisite licenses for motorcycle operation, with the majority (83%) accumulating over a decade of riding experience. Through analysis, a set of 39 items capturing nuanced behaviors exhibited by middle-aged motorcyclists in Thailand is identified. These items are categorized into four distinct clusters: speed violations, control errors, traffic errors, and adherence to safety equipment protocols. The utilization of the MRBQ in this study holds significant importance, as it provides valuable insights into the riding practices of the Thai population. The resultant findings hold the potential to inform safety initiatives and strategies aimed at enhancing the overall motorcycle riding experience.
Studies on the Germination and Emergence of Castor Seedlings
Authors: Severino Liv S.
Published: May 2024

Castor (Ricinus communis) is an oilseed usually cultivated in tropical and semi-arid conditions. The slow and uneven germination of castor seed is causing poor crop establishment and reduced seed yield. This series of studies investigated several factors influencing the time for castor seed germination and seedling emergence. Studies were made on the effect of seed coat permeability to water and the influences of temperature, morphology, and the hormone gibberellin. The best temperature for castor seed germination was near 31 °C, and the seed coat was permeable to water. The mechanical resistance of the seed coat was a mechanism controlling the germination of the castor seed. The time for germination was strongly associated with the seed coat relative weight, but it had little influence from other morphological characteristics. After the castor plants were subjected to three cycles of selection for fast germination, the seed weight was reduced, the caruncle became larger, and the seed coat became thinner. Gibberellin applied to the seed promoted a faster and higher germination rate. Pre-germination of the castor seed was not effective for promoting faster seedling emergence. Attempts to improve castor seed germination should integrate the many factors that influence this physiological process.
Accessing the Medicinal Potential of Mallotus philippensis: Comprehensive Exploration of Antioxidant and Antibacterial Properties through Phytochemical Analysis and Extraction Techniques
Authors: Ali Ahmad , Chen Hangping , Xu He , Wang Shuo , Yao Shun
Published: May 2024

Plants serve as reservoirs of bioactive compounds endowed by nature, rendering them promising subjects for investigating chemical diversity. Despite their potential, much remains untapped, whether in standardized extracts or isolated pure compounds. This unexplored terrain has paved the way for significant discoveries in pharmaceuticals. Notably, research has delved into the medicinal properties of Mallotus philippensis, a prominent plant in South Asia. Employing meticulous extraction techniques such as maceration, the fruit of this plant underwent initial antimicrobial screening, revealing encouraging results. Subsequent fractionation of the plant’s extracts via liquid–liquid extractions, utilizing dichloromethane and absolute ethanol, facilitated further analysis. Evaluating these fractions for antibacterial activity demonstrated efficacy against various pathogenic microorganisms, particularly Pseudomonas aeruginosa and Escherichia coli, notably by the ethanolic and dichloromethane extracts. Furthermore, a comprehensive phytochemical analysis unveiled the presence of alkaloids, flavonoids, saponins, glycosides, phenols, and tannins. An assessment of the extracts’ antioxidant potential via the 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging assay showcased significant activity, with a radical scavenging rate of 97%. This underscores the significance of utilizing fruit remnants, which are often rich in valuable chemical constituents yet commonly discarded, thereby adding value to both the species and the environment. Further investigation focused on the composition of Mallotus philippensis fruit, encompassing volatile and non-volatile metabolites through HPLC-MS analysis. Additionally, this study introduced the application of ionic liquid-loaded polysulfone microcapsules to enrich target constituents from crude extracts. An exploration of the key separation conditions, results, and recycling performance of these microcapsules provided insights for future research endeavors. Overall, this comprehensive study of Mallotus philippensis fruit extracts establishes a foundation for the ongoing exploration and development of this medicinal plant.
Early Identification of Olive Oil Defects throughout Shelf Life
Authors: Freitas Flávia , Cabrita Maria João , da Silva Marco Gomes
Published: May 2024

The unique aroma and flavor of extra virgin olive oil (EVOO) are generally associated with its volatile composition, which includes a variety of components responsible for positive attributes as well as sensory defects which result from chemical oxidation processes and the action of exogenous enzymes. In this study, a robust analytical method, headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME-GC/MS), was developed to tentatively identify volatile organic compounds (VOCs) as markers of positive and negative attributes, correlating them with relative percentages to estimate the risk of disqualification during the shelf life of EVOO. Significant differences (p < 0.05) were identified in the levels of VOCs over time, mainly those derived from the lipoxygenase (LOX) pathway. Principal component analysis (PCA) was applied to process the experimental data. The ratio of E-2-hexenal to acetic acid allowed for the prediction of the disqualification of monovarietal EVOO by the sensory panel.
Sustainable Purchasing Behaviors in Generation Z: The Role of Social Identity and Behavioral Intentions in the Saudi Context
Authors: Elgammal Islam , Ghanem Marwa , Al-Modaf Obaid
Published: May 2024

This study investigates the sustainable purchasing behaviors of Generation Z in Saudi Arabia, providing an insightful exploration by integrating the theory of planned behavior and social identity approach. Through qualitative research, the study uncovers nuanced insights into the motivational factors and social dynamics influencing eco-friendly consumer choices among young adults. It highlights the importance of environmental consciousness, peer influence, and identity-based motivations in shaping sustainable purchasing patterns. The findings reveal that Generation Z’s decisions are significantly influenced by a combination of personal attitudes, perceived social norms, and identity-related aspirations towards sustainability. This research broadens the current understanding of green consumption in a culturally specific context, suggesting that young consumers’ sustainable behaviors are deeply intertwined with their social identities and environmental awareness. The implications of these findings are significant for policymakers, marketers, and manufacturers aiming to encourage eco-friendly practices among younger generations, highlighting the need for tailored strategies that resonate with their values and social identities.
Air Pollution, Physical Exercise, and Physical Health: An Analysis Based on Data from the China General Social Survey
Authors: Li Fawei , Lu Chuntian , Li Ting
Published: May 2024

This study aims to investigate the influence of air pollution and physical exercise on residents’ health using data from the Chinese General Social Survey (CGSS) 2018. The research is based on the Grossman Health Production Function and employs the ordered logit model to analyze the relationship between air pollution, physical exercise, and residents’ health. We find that among the Chinese population aged 18 and above, air pollution negatively affects residents’ physical health, whereas physical exercise has a significantly positive effect. Introducing gender-stratified and urban–rural stratified models, the research reveals that the negative effects of air pollution on residents’ health vary among different groups. On one hand, men and residents living in urban areas will bear heavier health damages due to air pollution. On the other hand, physical exercise positively affect the health of both men and women, whether in rural or urban areas. Additionally, age and higher income are associated with better physical health, whereas education does not show a significant impact. Based on these findings, a series of policy recommendations have been proposed to comprehensively and systematically promote ecological governance and sustainable development. The government should strengthen environmental regulations, reduce residents’ exposure to air pollution risks, improve the equality of basic public services, invest in rural sports infrastructure, promote healthy lifestyles, and provide personalized health guidance through health education and mobile health services. Moreover, when formulating policies, the government should consider the specific needs of different groups to ensure the fairness and sustainability of the policies.
Sustainable Approach of a Multi-Hazard Risk Assessment Using GIS Customized for Ungheni Areal Situated in the Metropolitan Area of Iasi
Authors: Olteanu Ioana , Crenganiș Loredana Mariana , Diac Maximilian , Precul Alina Mihaela
Published: May 2024

Hazards associated with natural factors annually result in significant human and economic losses. An accurate and up-to-date assessment of various hazards can limit their impact and bring benefits both in the modeling phase and mostly in the risk mitigation plan stage. The article presents the results of a multi-hazard analysis that considers floods, landslides, and earthquakes carried out in the Ungheni area, located in the eastern part of Romania at the border with the Republic of Moldova. The research focused on producing harmonized hazard maps for the two countries since the area spreads jointly between the two countries. Common geospatial data were used for modeling and risk assessment, such as airborne laser scanners, global navigation satellite systems, rasters, and vectors from analog and digital sources. Among hazards, the flood maps for the studied area, Ungheni, were designed using 2D hydraulic modeling in HECRAS software (version 6.3.1); the landslide maps considered the ArcGis platform following Romanian methodology; and the seismic analysis collected onsite measurements on the built environment. The shared use of geospatial data in modeling the three hazards led to high accuracy of the results and determined their spatial homogeneity. It was observed that only two areas, Mînzătești and Coada Stîncii villages from Ungheni Areal, are highly vulnerable to all three hazards. The research findings, along with mitigation recommendations, have contributed to the development of a more precise action plan for natural hazards events by local authorities and decision-makers.
Exploration or Exploitation? Corporate Green Innovation Strategy for Carbon Emission Reduction-Evidence from Pilot Enterprises in China
Authors: Liu Shanshan , Li Yugang
Published: May 2024

Green innovation has become a key strategy for reducing emissions. However, existing research mainly examines this phenomenon through the resource and institutional perspectives, often ignoring the changes in corporate green innovation behavior under industry peer pressure. Therefore, this study draws on the policy framework of China’s carbon trading pilot and uses a multi-period difference-in-difference (DID) fixed effects model to explore how carbon trading shapes enterprises’ green innovation strategies. The survey used data from pilot enterprises from 2008 to 2019 and found that carbon trading policies are conducive to green innovation, and both exploratory green innovation and exploitative green innovation have been reflected. It is worth noting that under the influence of peer pressure, this positive effect is more prominent in exploratory green innovation. Furthermore, it was found that firms facing carbon pressure can skillfully find an equilibrium between exploratory green innovation and exploitative green innovation. The research results demonstrate the green innovation strategies and trade-offs of Chinese enterprises facing the impact of carbon trading policies, with the hope that the research conclusions will have certain theoretical reference significance for future corporate green transformation and increased investment in green innovation.
Dialogue and Disruption at the Doorstep: Participant Perceptions during a City Walk as a Climate Communication Format
Authors: Hartmann Elisabeth , Geneuss Katrin , Hoppe Imke
Published: May 2024

Since there is a broad empirical consensus that linear science communication focusing on disaster framing rarely empowers audiences and prompts transformative action, alternative climate communication formats are needed. This paper explores an alternative climate communication format, which integrates the issue into a local context (Munich, Germany) via transdisciplinary cooperation, specifically through collaboration with local climate educators and tapping into the scientific expertise of local stakeholders. The conceptualized format of a City Walk on the subject of climate justice addresses urban citizens and tests the effectiveness of climate justice as an alternative framing. Drawing on an accompanying empirical study with qualitative group discussions (n = 14, October 2023), this article explores how the format and framing are perceived by the participants. Based on these findings, we discuss the potentials and pitfalls of the format for transdisciplinary science communication. In summary, the City Walk deepened participants’ understanding of local climate justice—that is to say, how heat and flooding could amplify existing inequalities, and why adaptation and mitigation measures have not yet been implemented more thoroughly. Here, the crucial point is not whether the shift from climate change being a general topic to a personal one is supported by technical aspects of communication (e.g., virtual simulations). However, perceived local climate justice barriers (like bureaucracy) led participants to prioritize individual action (‘footprint’) over collective action (e.g., addressing local change). With these results, this study underlines the importance of new transdisciplinary formats for climate communication to address local change.
Formulating Eco-Friendly Strategies: Transition to Green Economy
Authors: Kadioglu Irfan , Gurbuz Ismail Bulent
Published: May 2024

Turkey is attempting to achieve carbon neutrality targets by implementing environmentally friendly techniques. This study aims to assess the short- and long-term relationships between Turkey’s annual carbon emissions and economic growth, as well as annual electricity generation from renewable fossil fuels. Data for this study were obtained from the World Bank and the official website of the Turkish Statistical Institute (TURKSTAT) from 1986 to 2020. The Autoregressive Distributed Lag Bound Test (ARDL) technique was used to estimate variable cointegration. The cointegration test shows a long-run relationship between the selected variables. A 1% increase in the GDP, COAL, and PTRLGZ variables increases CO2 emissions by 0.65%, 33%, and 7%, respectively. The RE variable was found to have a negative effect on CO2 emissions. The effect of the RE variable on CO2 emissions is −0.10. This result indicates that a 1% increase in the RE variable reduces CO2 emissions by 0.10%. Looking at the short-term data, the error correction coefficient (CointEq (−1)) was found to be negative (−0.832) and significant. Based on the error correction variable, it is expected that the short-run deviations from equilibrium will be corrected and that a long-run equilibrium will be reached in less than one year. The long-run results also suggest that the factors used in the model have a statistically significant effect on the dependent variable. While this effect is negative for annual electricity production from renewable energy sources, it is positive for annual electricity production from fossil fuels and gross domestic product (GDP).
Indigenous Intergenerational Resilience and Lifelong Learning: Critical Leverage Points for Deep Sustainability Transformation in Turbulent Times
Authors: Williams Lewis
Published: May 2024

Rapidly changing conditions and the complexity and interconnectedness of global challenges means that learning across the lifespan is more important than ever. Equally critical are sustainable planetary futurities and associated pedagogical practices which reach beyond the imposition of settler temporalities, modernist technological solutions, and western cognitive imperialism as a means of responding to our cultural-ecological crisis. Pedagogical practices must actively work with diverse generational realities and impacts associated with the cultural, ecological, and climate emergency. This paper reports on a growing conversation across diverse cultural biospheres regarding inclusive Indigenous-led strategies of multi-generational resilience addressing human–environmental wellbeing. Adopting an inclusive Indigenist theoretical and methodological approach, it narrates the epistemological and relational practices of several multigenerational pedagogical forums (land-based and virtual) based in and out of Turtle Island/Canada from 2015–2023. Based on an Indigenist research paradigm and qualitative research methods pertaining to one multi-day land based learning summit and three online virtual learning forums, a thematic analysis of key findings relating to pedagogical practices, intercultural and intergenerational themes, and the shifting dynamics of multi-generational resilience work is provided. Themes include the critical importance of epistemological shifts over time; Indigenous multi spatial-temporalities; relational rather than binary or even hybrid views of sexual, gendered, ethnic, and racial identities within cultural-ecological restoration work; the relevance of transnational gatherings; and the adaption of pedagogical practices to meet fluctuating local–global conditions. The paper then summarizes the key elements of lifelong learning within an Indigenist approach to cultural-ecological restoration work, and concludes with a discussion regarding the relevance of this approach in reorientating three previously identified leverage points for accelerating sustainability transformation.
Architectural Detail in Sustainable Architecture: Formal and Aesthetic Connotations
Authors: Celadyn Waclaw , Celadyn Magdalena
Published: May 2024

Contemporary architecture is shaped by the paradigm of sustainability and is characteristic of many solutions determined by a relevant set of principles related to shaping the environment based on the ecology of systems focused on the flow of energy. These design principles concern gaining energy from renewable resources, protection against the loss of thermal energy from buildings, protection against the excess of thermal energy in buildings, and proper distribution of thermal energy in buildings. This paper presents a proposal for a method to analyze some building components used as sustainability-related elements given their formal similarity to historic architectural details or some artworks integrated with buildings. It aims to emphasize the potential of a different perspective from which to perceive and assess buildings, and specifically their architectural details, given their spatial and aesthetic values associated with sustainable technical solutions. This study is based on a few differentiated examples. It proves the relations mentioned above true, given the sustainability paradigm epitomized in technical solutions to contemporary buildings and the related aesthetic features characterizing the relevant architectural detailing. Such a perception of buildings is intended to promote unconventional viewing and assessment of them by the public and professionals in the area of architecture and art. It would make them discover new types of aesthetic values, which are usually invisible.
Interpersonal and Intrapersonal Skills for Sustainability in the Educational Robotics Classroom
Authors: Llanos-Ruiz David , Ausin-Villaverde Vanesa , Abella-Garcia Victor
Published: May 2024

Education is an indispensable tool for improving social sustainability. In the school context, a wide variety of methodologies are being considered to achieve this goal by promoting cultural and experiential sustainability through educational and technological innovation. Educational robotics is an educational–formative context that makes it possible to develop new learning environments, enhance sustainable curriculum development, and promote active student participation. The general objective of this research is to analyze the perceptions of teachers of technology, robotics, and/or programming and to study the social benefits of interpersonal, intrapersonal, and/or academic skills of students to improve curricular sustainability during the teaching–learning process from the perspective of robotics and programming in students in early childhood education, primary education, compulsory secondary education, and other educational levels in formal and non-formal education. The study sample included 115 teachers of technology, programming, and/or robotics (50.4% male, 49.6% female). The research was carried out using a quantitative, retrospective, and cohort methodology through a cross-sectional, non-experimental, and non-longitudinal study over time. A questionnaire specifically designed to collect data from the participating teachers was used. According to the results obtained, educational robotics is a multidisciplinary learning tool that enhances the development of skills such as personal autonomy, collaborative work, and emotional management, motivates the acquisition of knowledge based on practice, promotes curricular sustainability, and creates a new learning context where the teacher is the formative guide of the students and the students are engaged in their own learning.
The Role of Data-Driven Agritech Startups—The Case of India and Japan
Authors: Suresh Divya , Choudhury Abhishek , Zhang Yinjia , Zhao Zhiying , Shaw Rajib
Published: May 2024

Global climate change poses many threats, with significant consequences for crop productivity and food security. The agricultural sectors in India and Japan face multiple problems, such as pre-harvest problems (volatility in input prices), post-harvest and supply chain issues in India, and labor shortages, the aging workforce, and the increase in the food self-sufficiency ratio, among others, in Japan. Farming practices and productivity can be improved by employing data-driven insights. This study was primarily conducted using secondary data collection and a literature review to comprehend the current state of data-driven agriculture in India and Japan, including analysis of supporting government policies and patent trends. The same context was further explored by conducting semi-structured interviews with key persons from data-driven agritech startups (capabilities, value proposition, etc.) in India and Japan. The results show that the driving forces of agritech adoption are sustainability, evolving business models, regulations, and macroeconomic conditions. On the one hand, India’s agriculture ecosystem is facing volatility in input prices, inefficient supply chains, low access to technology, limited access to finance, and the lack of dependable agricultural information, while Japan is tackling an aging farming workforce, high production costs, and the need for technological innovation. The findings show that by leveraging bilateral collaboration, agritech startups from India and Japan can mutually benefit from driving innovations in the agritech space as India could maxmize its digital potential by leveraging Japan’s digital prowess, and Japan could expand its market base and reap benefits from the enormous agritech potential India.
Reuse of Steel Residue in Polypropylene Matrices for the Production of Plastic Wood, Aiming at Decarbonization
Authors: Ribeiro Leticia S. , Silva Ana Lúcia Nazareth da , Amario Mayara , Stolz Carina M. , Haddad Assed N. , Boer Dieter Thomas
Published: May 2024

According to a 2024 World Economic Forum survey, climate change is the primary concern for the future. To address these challenges, adaptation measures and actions to reduce or avoid greenhouse gas emissions are necessary. Emissions from the waste management sector rank as the seventh-largest contributor to global emissions. Efforts are underway to decarbonize steel processes and promote waste reuse. “Fluff”, generated during ferrous scrap processing, poses reuse challenges due to its characteristics. This study evaluates the production of wood–plastic composites using polypropylene and “Fluff” to address environmental concerns and reduce greenhouse gas emissions. Methodologically, waste characterization preceded the extrusion of waste and polypropylene blends at varying compositions. The resulting materials were pelletized, molded, and characterized. CO2 emission reductions from waste diversion from landfills were assessed under two scenarios. In Scenario 1, emissions totaled 19,054 tons/year, while in Scenario 2, with gas capture and utilization, emissions reached 10,617 tons/year for 20,000 tons of waste annually. Composite characterization revealed favorable properties, suggesting viability for wood–plastic production. This approach supports industrial decarbonization and circular economy initiatives in the steel sector.
Dynamic Capability in Business Ecosystems as a Sustainable Industrial Strategy: How to Accelerate Transformation Momentum
Authors: Banka Kenichiro , Uchihira Naoshi
Published: May 2024

From a sustainable development perspective, continuous industrial growth is an important issue. In recent years, it has become difficult for companies to survive in an increasingly competitive and rapidly changing business environment. To align with these changes, companies must not only rapidly transform their own organizations but also their current business domains. However, it is difficult for a leading company alone to transform existing business domains. While it is known that the transformation of a business area requires cooperation with partners, the mechanism of sustainable growth in existing business ecosystems is unclear. To solve this problem, this paper aims to unveil the role of transformation momentum in the business ecosystem in the IT (information technology) industry, which is rapidly changing from traditional IT services to cloud-based services. This study has selected Amazon Web Services (AWS) and Microsoft Azure as IoT case studies, as these cases have successfully transitioned from their original business domains to new ones. Based on these cases, we established a Sustainable Business Ecosystem Transformation (SBET) model for transforming industries using the business ecosystem’s dynamic capabilities. The SBET model demonstrates how transformation momentum can be created using business ecosystems in four phases (Exploration, Creation, Formation, and Mutation). The SBET model contributes to expanding the business ecosystem concept by adopting sustainable growth and accelerating transformations to enhance global IT business ecosystems. Using the model in this study, companies can achieve continuous growth not only in their own organizations but also in their partners in the wider business domain.
Carbon and Sulfur Isotope Methods for Tracing Groundwater Contamination: A Review of Sustainable Utilization in Reclaimed Municipal Landfill Areas
Authors: Porowska Dorota
Published: May 2024

Reclaimed landfill areas are excluded from various development options including construction, while contaminated zones around such places have no such restrictions. The successful reclamation of landfills means that the old landfill visually fits in well with its surroundings, but soil and water contamination problems remain valid. Former landfills were built without properly preparing the land, which resulted in the migration of contaminants in groundwater for a long period after these landfills were closed, further resulting in the limited use of such areas, at least for some purposes. Due to the development of cities, landfills formerly located in suburbs are becoming a part of these cities. In order to optimally and safely use these spaces, knowledge regarding the quality of the soil and water environment is necessary. This article presents methodological considerations regarding the use of carbon and sulfur isotope methods to assess groundwater contamination around former municipal waste landfills, especially reclaimed municipal landfills. It has been shown that natural groundwater is characterized by low values of both δ13CDIC and δ34S (δ13CDIC from −20 to −10‰ and δ34S at approximately −5‰), whereas leachate-contaminated groundwater is characterized by high values of both parameters (δ13CDIC from −10 to + 5‰ and δ34S from +5 to +20‰). The aim of this article is to demonstrate that carbon and sulfur isotope methods extended via SWOT analysis are universal and reliable methods for assessing the migration of pollutants, thus facilitating decisions regarding management.
Methylobacterium symbioticum Applied as a Foliar Inoculant Was Little Effective in Enhancing Nitrogen Fixation and Lettuce Dry Matter Yield
Authors: Arrobas Margarida , Correia Carlos M. , Rodrigues Manuel Ângelo
Published: May 2024

Nitrogen (N) is a limiting ecological factor for plant growth in most agroecosystems. Biological N fixation, especially from nodulated legumes, has been promoted in recent decades as an alternative or complement to industrially synthesized N fertilizers. The possibility of utilizing N-fixing organisms from the phyllosphere that demonstrate effectiveness across a wide range of crops is particularly exciting. In this study, we examined the N-fixing capacity and the impact on lettuce growth of an inoculant recently introduced to the market, which contains the microorganism Methylobacterium symbioticum and is recommended for various cultivated species. A pot experiment was conducted using a factorial design, which included the inoculant (No and Yes) and four N rates (0 (N0), 25 (N25), 50 (N50), and 100 (N100) kg ha−1 of N), with four replicates, over four lettuce growing cycles. The inoculant had a significant effect on dry matter yield (DMY) only during the second of the four growing cycles. The mean values of the four growing cycles ranged from 9.9 to 13.7 g pot−1 and 9.9 to 12.6 g kg−1 in pots that received and did not receive the inoculant, respectively. On the other hand, plants exhibited a robust response to N applied to the soil, showing significant increases in both DMY and tissue N concentration across all growing cycles. Mean values of DMY in the treatments N0 and N100 ranged from 5.6 to 8.9 g pot−1 and 12.5 to 16.1 g pot−1, respectively. N concentration in tissues varied inversely with DMY, indicating a concentration/dilution effect. The difference in N concentration between treated and untreated plants, used as an estimate of fixed N, was very low for each of the soils’ applied N rates, assuming average values for the four growing cycles of −1.5, −0.9, 2.4, and 6.3 kg ha−1 for N0, N25, N50, and N100, respectively. This study emphasized the low amount of N supplied to lettuce by the inoculant and its limited effect on DMY. Generally, in biological systems with N-fixing microorganisms, achieving high fixation rates requires a high level of specificity between the microorganism and host plant, a condition that seems not to have been met with lettuce. Considering the importance of the subject, is imperative that further studies be conducted to determine more precisely in which crops and under what growing conditions the inoculant proves to be a valuable input for farmers and an effective method for reducing N mineral fertilization.
Deep Learning-Based Truthful and Deceptive Hotel Reviews
Authors: Gupta Devbrat , Bhargava Anuja , Agarwal Diwakar , Alsharif Mohammed H. , Uthansakul Peerapong , Uthansakul Monthippa , Aly Ayman A.
Published: May 2024

For sustainable hospitality and tourism, the validity of online evaluations is crucial at a time when they influence travelers’ choices. Understanding the facts and conducting a thorough investigation to distinguish between truthful and deceptive hotel reviews are crucial. The urgent need to discern between truthful and deceptive hotel reviews is addressed by the current study. This misleading “opinion spam” is common in the hospitality sector, misleading potential customers and harming the standing of hotel review websites. This data science project aims to create a reliable detection system that correctly recognizes and classifies hotel reviews as either true or misleading. When it comes to natural language processing, sentiment analysis is essential for determining the text’s emotional tone. With an 800-instance dataset comprising true and false reviews, this study investigates the sentiment analysis performance of three deep learning models: Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Recurrent Neural Network (RNN). Among the training, testing, and validation sets, the CNN model yielded the highest accuracy rates, measuring 98%, 77%, and 80%, respectively. Despite showing balanced precision and recall, the LSTM model was not as accurate as the CNN model, with an accuracy of 60%. There were difficulties in capturing sequential relationships, for which the RNN model further trailed, with accuracy rates of 57%, 57%, and 58%. A thorough assessment of every model’s performance was conducted using ROC curves and classification reports.
Sustainable Development in Gansu Province: Theil Index and Cluster Analysis
Authors: Cao Peng , Tao Haijun
Published: May 2024

With the advancement of the rural revitalization strategy, counties have emerged as vital platforms for supporting rural revitalization, underscoring the increasing importance of sustainable development in their economies. It is imperative to evaluate the sustainable development potential of county economies and implement precise measures accordingly. This paper selects relevant economic development indicators from 2016 to 2020 for 76 counties in Gansu Province, constructs an evaluation system for assessing their sustainable development potential, and employs methods such as the Theil index, spatial autocorrelation, principal component analysis, and cluster grouping classification. The evaluation considers three aspects: the county economic development gap, the development potential score, and cluster analysis. The findings reveal that the economic development of Gansu Province’s counties exhibits spatial characteristics of multi-point flowering and scattered distribution, with relatively weak communication and development between surrounding counties. Over the five-year period, significant disparities in economic development among Gansu Province’s counties are evident. Liangzhou District ranks highest in county economic development, while other counties with robust economic development are primarily concentrated in the Lanzhou–Baiyin metropolitan area, the Tianshui metropolitan area, the west entrance of the Hexi Corridor economic belt, and the Qingyang–Pingliang group area. These counties exhibit a spatial pattern of agglomeration towards the central and eastern regions. Moreover, some counties in the southeastern region of Longdong demonstrate promising economic development potential, forming an initial scale of contiguous development. This indicates favorable prospects for sustainable development in the region’s county economy.
Analysis of Consumer Preferences for Green Tea Products: A Randomized Conjoint Analysis in Thai Nguyen, Vietnam
Authors: Hong Bui Xuan , Ichihashi Masaru , Ngoc Nguyen Thi Bich
Published: May 2024

How local economies can successfully develop remains an important issue for any developing country. One mechanism for promotion of economic development is government-driven policy. The problem is that it is not clear whether public-led economic promotion attracts consumers and which promotion factors are relatively significant for boosting particular goods. This paper examines attributes of green tea products likely influencing consumer preferences, focusing on the Thai Nguyen area in Vietnam as an example. In this area, the “One Commune, One Product” (OCOP) project has been implemented by the local government. This study employs randomized conjoint analysis based on data collected from 450 randomly selected consumers in several local supermarkets. Interestingly, the results show that online style sales have a negative preference for the purchase of green tea products, while transparency, such as the traceability of the product and product information, and reliability, such as certification, enhance the purchase of these products by consumers. However, this finding is not necessarily robust because our results indicate that approximately 90% of consumers tend to choose the default pair, which means that they do not actively prefer the product, possibly implying that this kind of public-led promotion is not yet broadly familiar to all people.
CFD-DEM Modeling of Cryogenic Hydrogen Flow and Heat Transfer in Packed Bed
Authors: Quan Xin , Xia Yongfang , Zhang Quanchen
Published: May 2024

Hydrogen is an important component of renewable energy and is essential for sustainable development. The cryogenic energy storage system can solve the problem of hydrogen storage. A packed bed can be applied in a cryogenic energy storage system. It is crucial to understand the cryogenic energy discharging in a packed bed. In the present work, the CFD-DEM coupling method is used to investigate the pore-scale flow and heat transfer characteristics of cryogenic hydrogen flowing through the packed bed. To demonstrate the characteristics of the pore-scale heat transfer of the hydrogen flow in a packed bed, the local radial-averaged and axial-averaged temperatures and velocities are analyzed in detail, depending on the local porosity distribution. The pore-scale radial-averaged velocity distribution is proportional to the local radial porosity distribution, whereas the pore-scale radial-averaged temperature characteristics are inverse. Moreover, for the heat exchange of the cryogenic hydrogen flow in a packed bed, it can be found that the cryogenic hydrogen flow is fully heated at an axial distance of approximately 7 dp. Finally, considering that the thermo-physical properties of cryogenic hydrogen are sensitive to the temperature in a packed bed, the friction factor and Nusselt number in the packed bed are also analyzed under various operating parameters, which are in good agreement with certain classic empirical correlations.