bluuebunny/crossref_metadata_2025 huggingface dataset:
Can Cryptocurrencies Be Green? The Role of Stablecoins Toward a Carbon Footprint and Sustainable Ecosystem
Authors: Koemtzopoulos Dimitrios , Zournatzidou Georgia , Sariannidis Nikolaos
Published: January 2025

(1) Background: Cryptocurrencies have a substantial environmental impact. In particular, the mining procedure that is employed to produce and finalize the transaction is energy-intensive and generates carbon emissions. Consequently, the objective of the present investigation is to investigate the function of cryptocurrencies in a sustainable development. This research specifically investigates the function of stablecoins, a novel subject in finance and academia that has the potential to foster a sustainable business environment. (2) Methods: A bibliometric analysis was performed using the R statistical programming language together with the bibliometric tools Biblioshiny and VOSviewer to fulfill the research objective. Data were obtained from the Scopus database, and their selection was completed using the PRISMA methodology. (3) Results: The results of the current research highlight the crucial role of stablecoins in promoting an alternative decentralized financial sector, offering a unique opportunity for the market to create a more inclusive and environmentally friendly financial ecosystem. Moreover, research indicates that stablecoins might convert Ethereum into a stable currency and enhance their ecologically friendly path. (4) Conclusions: Stablecoins have become a crucial tool in the unpredictable bitcoin environment, offering stability in a tumultuous market. The research indicates that users need to acknowledge the sustainability of asset collateral, and so far, only the regulation of stablecoins is progressing in this area.
Democracy in the Phutai Ethnic Group Community in Kalasin Province, Thailand
Authors: Khuenkhaew Yuttapong , Phromlah Wanida , Chueasakhoo Chinawat , Singhapat Suchanart
Published: January 2025

The study aims to understand the processes of democracy in the Phutai ethnic group community in Kalasin Province. This would help with defining the complex and critical issues of democracy processes in the Phutai ethnic group community, and then enabling it to reveal the guidelines to strengthen democracy in the Phutai ethnic community and progress towards local community development. Additionally, the research also proposes ways for knowledge exchange and network building regarding democracy development among Phutai ethnic communities in Kalasin and other provinces in Thailand. The research is qualitative, focusing on Phutai ethnic communities with diverse contexts, including urban, semi-urban, rural, and mixed-ethnic communities existing in eight districts of Kalasin Province, where it is one of the main home provinces to Phutai communities in Thailand. Data were gathered through a variety of sources, including academic literature reviews, research reports, in-depth interviews, and focus group discussions. The key informants for in-depth interviews and focus group discussion were recruited by their specific extensive related experience, who are Phutai people. The data collected from these diverse sources were then used for a descriptive analysis to ensure accurate and comprehensive research findings. This study found that the model and process of democracy in ethnic communities in Kalasin Province are a hybrid form, relying on democratic processes rooted in the community to build consensus or approval, which leads to actions that align with government policies and meet the needs of the community. This is achieved through a form of democratic political culture based on ethnonationalism, which contributes to significant democracy within the community. For promoting knowledge exchange and building networks, the research emphasizes the critical need for the precise legal recognition of rights of Phutai ethnic communities and also the need for various methods of information dissemination among all generations of the Phutai group in Kalasin Province and other areas.
Fairtrade in Peru: Challenges and Opportunities for Sustainable and Equitable Agricultural Development
Authors: Lozano Paredes Dina Lucila , Okada Saavedra Hiromi , Moscoso Cuaresma Julio Ricardo , Azabache Moran Carlos Alberto , Delgado Katherine Norma del Pilar Yesquén , Diaz Cruz Mirella Esther , Salazar Seminario Vania Lucia , Pastor Pinto Jhosep , Amer Layseca Tarek
Published: January 2025

Fairtrade, present in Peru since 1990, has been widely studied for its impact on agri-food production. This research, based on convenience surveys conducted with leaders and members of cooperatives and agri-exporting companies during the 2024 Peruvian Expoalimentaria fair, examines the benefits and challenges faced by producers in their pursuit of sustainable and equitable development. The results were statistically analysed using Cronbach’s alpha, factor analysis, and the ordinal logistic regression model. These methods revealed that not all the dimensions evaluated reached statistical significance. However, the dimensions of agricultural sustainability and social justice emerged as the most significant, driven by the adoption of sustainable technologies and democratic participation in cooperatives. Nonetheless, these dimensions require additional external conditions to ensure well-being, such as market incentives, which did not achieve statistical significance, suggesting the influence of contextual factors not accounted for in the study. This research not only enriches the existing literature but also provides recommendations for implementing Fairtrade initiatives in Peru to promote more equitable and sustainable agricultural development that improves the socio-economic and socio-political conditions of the most disadvantaged producers. Furthermore, this study highlights the need to expand the theoretical development of unexplored variables, such as association models, sustainable practices, and economic growth in rural communities. In this way, it serves as an exploratory foundation for future public policies and strategies in the agri-food sector.
Applications of Digital Technologies in Promoting Sustainable Construction Practices: A Literature Review
Authors: Li Yuanyuan , Zhao Xiujuan , Liu Chunlu , Zhang Zhigang
Published: January 2025

In recent years, the applications of digital technologies in sustainable construction have gained increasing interest. However, no comprehensive literature review has been conducted. Thus, this paper analyzes 990 relevant articles in this regard published from 2014 to 2023 by using CiteSpace (version 6.3.R1) and HistCite (version Pro 2.1) and identifies the most influential journals, institutions, and regions. The knowledge base was detected through a cluster analysis, which concentrates more on seven core themes: barriers, energy efficiency and building energy performance, life cycle assessment, computer vision, renovation, building sustainability assessment, and management. A citation analysis revealed that the applications of digital technologies were based in four dimensions of sustainable construction: environmental, social, and economic performance and green building assessment are the current hotspots. Finally, the potential future research trends in this field were proposed: (1) strengthening research on the application of more digital technologies; (2) expanding the use of digital technologies in the Operation and Maintenance (O & M) and demolition phases; (3) deepening the research on multi-objective optimization; and (4) exploring how to overcome obstacles. The findings provide highly valuable information for researchers with current research ideas and future directions in this field. This paper also has the potential to deepen practitioners’ comprehension of optimal digital technologies for bolstering construction sustainability.
Mitigation Matrix for Improving Material Management Sustainability Within Construction in the Middle East
Authors: Ruzieh Abdulla Subhi
Published: January 2025

The construction industry in the Middle East faces significant challenges, including low productivity, substantial material waste, and inefficient deliveries, with limited research addressing the relationship between these challenges and critical success factors (CSFs). This study explored mitigation strategies to enhance productivity, competitiveness, and sustainability in the construction sector of the region. Using data from 92 questionnaires collected from industry stakeholders, descriptive and bivariate analyses were employed to identify correlations between variables using SPSS and Excel. The findings map out the challenges affecting material management and their correlation with CSFs, offering innovative solutions to address these issues. For example, this study highlights how poor communication leads to problems, such as change orders and inaccurate drawings, which can be mitigated by improving coordination and collaboration and adopting appropriate ICT tools. The practical mitigation matrix presented in this work provides actionable strategies for effectively overcoming challenges and implementing CSFs. While contextualised for the Middle East, the findings have broader relevance for global construction practices, with careful consideration required for application in different contexts. Importantly, this study advances sustainability by promoting resource efficiency, minimising waste, and fostering effective practices to support sustainable construction across the region.
Environmental and Human Health Risks of Estrogenic Compounds: A Critical Review of Sustainable Management Practices
Authors: Lerdsuwanrut Nisha , Zamani Reza , Akrami Mohammad
Published: January 2025

The concentrations of estrogens and xenoestrogens in the environment are rising rapidly, posing significant and multifaceted risks to human health and ecosystems. It is imperative for governments to develop policies that leverage sustainable technologies to mitigate the presence of pharmaceutical estrogenic compounds in the environment. This review examines the global environmental and human health risks associated with indigenous estrogens and synthetic pharmaceutical xenoestrogens, while critically evaluating sustainable approaches to their management. A total of 28 studies, published between December 2013 and 18 January 2024, and sourced from PubMed and Scopus, were systematically reviewed. Most of these studies focused on estrogenic compounds in aquatic environments where they contribute to reproductive and developmental abnormalities in fish and may enter the human food chain, primarily through fish consumption. Sustainable methods for removing or neutralizing estrogenic compounds include adsorption, filtration, and enzymatic degradation. Additionally, technologies such as activated sludge processes and high-rate algal ponds demonstrate promise for large-scale applications; however, further research and standardized operational guidelines are needed to optimize their efficiency and sustainability. This review has concluded that ECs can have severe consequences on the environment, most notably, impairment of reproductive functions in fish and humans, underscoring the urgent need for governments to implement drug take-back programs, establish evidence-based guidelines for wastewater and pharmaceutical waste treatment, and set enforceable thresholds for estrogenic compounds in surface and drinking water. Existing regulations such as the UK’s Regulation on the registration, evaluation, authorization, and restriction of chemicals and the United States’ National Primary Drinking Water Regulations can be modified to include ECs as dangerous chemicals to aid in maintaining safe EC levels”. Such measures are critical for reducing the environmental concentrations of pharmaceutical estrogenic compounds and safeguarding both public health and ecological integrity.
Assessment of Indoor Classroom Environment Quality Associated with Student Sleepiness: Pathways Towards a Sustainable Environment Through a Pilot Study
Authors: Andrade Alexandro , D’Oliveira Anderson , Branco Joaquim Henrique Lorenzetti , Russi Aldo , Stabile Luca , Buonanno Giorgio
Published: January 2025

Student sleepiness during classes is a frequently reported condition that can impair performance in the teaching–learning process and is even unsustainable for health. Although the environmental quality of the classroom may affect the students’ sleepiness, studies that exhaustively investigate the relationship between indoor environmental quality (IEQ) and sleepiness levels in classrooms are lacking. To this end, in the present paper, we carried out an experimental pilot study involving twenty-seven Italian adolescent students to determine the increase in their sleepiness rate during the school period utilizing the Epworth Sleepiness Scale (ESS). The analysis was performed in a classroom in which the indoor environmental quality was monitored, including measurements of the thermal comfort, sound pressure level, illuminance, carbon dioxide (CO2) concentrations, and airborne particle concentrations (both sub-micrometric particles and PM10). Three measurement days were considered. The results showed that student sleepiness significantly increased during the school period (Day 1 p = 0.00, Day 2 p = 0.03, and Day 3 p = 0.03). This increase was observed on measurement days characterized as having both perceived higher and lower thermal comfort and even in the presence of limited exposure to airborne particle concentrations, presenting an association with the high indoor concentration of CO2 detected in the classroom (Day 1 between 978 and 3261 ppm; Day 2 between 1044 and 2338 ppm; Day 3 between 1116 and 2623 ppm), due to reduced ventilation rates and the students’ sleepiness. Thus, the findings suggest that adequate ventilation rates can limit the increase in the rate of sleepiness, indicating, from our pilot study, that recommendations of sustainable environmental practices through comprehensive feasibility studies can promote positive changes in indoor environments such as classrooms.
Veterans’ Perceptions of Shared Autonomous Electric Shuttles: A Pre- and Post-Exposure Assessment
Authors: Wandenkolk Isabelle , Classen Sherrilene , Mason Justin , Hwangbo Seung Woo
Published: January 2025

Veterans often face transportation barriers, but advances in technology enable real-world testing of shared autonomous electric vehicles as potential energy-efficient solutions. While previous research has assessed civilians’ perceptions of autonomous vehicles (AVs), veterans—due to unique military experiences and health conditions—represent a distinct demographic. This study investigates veterans’ perceptions of autonomous shuttles (ASs) to assess whether these innovations may foster sustainable transportation behaviors. Leveraging data from the Autonomous Vehicle User Perception Survey (AVUPS), this study assessed AS perceptions among 77 veterans across four Florida cities before and after exposure. Results indicated significant increases in intention to use and total acceptance and a decrease in perceived barriers, with no change in well-being. Urban veterans showed improvements across multiple subscales, while rural veterans only showed reduced perceived barriers. Those with initially low total acceptance scores demonstrated greater improvements, particularly in intention to use and perceived barriers. The analysis of survey items showed increased trust, greater willingness to multitask, improved safety perceptions, and reduced concerns about declining driving abilities and hesitations toward AVs, with the latter three items remaining significant after correction. Overall, AS exposure positively influenced veterans’ perceptions, and the results point to the potential of ASs as a sustainable transportation option for veterans.
The Development of Economic–Social–Ecological Complex Systems in the Yellow River Basin, China
Authors: Li Yuyang , Hao Haiguang , Sun Lihui , Liu Mengxiao , Wang Ding
Published: January 2025

The economic, social and ecological elements in the region constitute a complex ecosystem. The development trend, internal coordination and interactive effects of the economic–social–ecological (ESE) system have consistently constituted pivotal scientific propositions in the context of the social development process. The Yellow River Basin holds strategic importance, acting as both an ecological barrier and a center for economic development within China. Based on these considerations, this study focuses on the Yellow River Basin and innovatively establishes a theoretical framework and measurement model for the development of the ESE system. Quantitative methods, including the coupled coordination model and augmented regression tree model, are employed to evaluate the development, coordination, spatial patterns and influencing factors of the ESE system in the study area. The findings reveal that the economic and social subsystems are rapidly developing. Over the study period, the focus of ESE system development shifted eastward. Furthermore, there were noticeable disparities in the factors influencing coordinated ESE system development across the upper, middle and lower reaches of the Yellow River Basin. Thus, sustainable development policies for the region must be tailored to local conditions. This study also offers insights into the potential development paths for the Yellow River Basin and other river basins in China, contributing practical value to the promotion of sustainable development and the construction of an ESE system that reflects the unique characteristics of the Yellow River Basin.
The Yield Estimation of Apple Trees Based on the Best Combination of Hyperspectral Sensitive Wavelengths Algorithm
Authors: Qin Anran , Sun Jiarui , Zhu Xicun , Li Meixuan , Li Cheng , Wang Ling , Yu Xinyang , Jiang Yuanmao
Published: January 2025

Agriculture’s sustainable growth necessitates the application of advanced science and technology to ensure the sensible use of resources and improve the agricultural economy’s long-term stability. In this study, apple trees were employed as research objects throughout the spring (NSS) and autumn shoot stop-growing stage (ASS), and the data source was canopy hyperspectral data of fruit trees collected using ASD near-earth sensors, which was then combined with multiple sensitive wavelength screening algorithms and machine learning models to create an efficient and accurate apple yield estimation system. This is critical for guiding fruit farmers’ production, maintaining market supply and demand balances, fostering stable agricultural economy development, and providing a scientific basis and technical support for agricultural sustainability. Firstly, the fruit tree canopy hyperspectral data and apple tree yield data were collected, and the Savitsky–Golay convolution smoothing method (SG) was used to preprocess the canopy hyperspectral data. Secondly, six algorithms—Competitive Adaptive Re-weighting Sampling (CARS), Genetic Algorithm (GA), Successive Projections Algorithm (SPA), Uninformative Variable Elimination Algorithm (UVE), Variable Iteration Spatial Shrinking Algorithm (VISSA), and Variable Combination Population Algorithm (VCPA)—were employed to screen for the sensitive wavelengths related to apple tree yield, then preferring three methods for two-by-two combinations to determine the optimal algorithm combinations. Finally, using the best algorithm combinations, we built the apple yield linear model partial least squares regression (PLSR) and three machine learning models, Random Forest (RF), Cubist, and XGBoost, to screen for the best estimation model. The results demonstrated that ASS was the best fertility period for estimating yield; the validation set of the model constructed using each algorithm in ASS had a higher R2 of 0.05–0.51 and a lower RMSE of 0.21–5.33 than those in NSS. The three algorithms preferred were CARS, GA, and VISSA. After combining the three algorithms in two combinations, the best combination of VISSA-CARS was found. The RF model established based on the best VISSA-CARS combination algorithm is the best model for apple yield estimation, with a validation set R2 = 0.78 and RMSE = 6.03. The findings of this study may provide a new concept for accurately and quickly estimating apple yield, allowing fruit growers to improve production efficiency and promote agricultural sustainability.
Encapsulated LyeTx III Peptide: Cytotoxic Agent Isolated from Lycosa erythrognatha Spider Venom
Authors: Santos Daniel Moreira dos , Santiago Livia Ramos , Santos Nayara Araújo dos , Romão Wanderson , Resende Jarbas Magalhães , de Lima Maria Elena , Borges Márcia Helena , Ribeiro Rosy Iara Maciel de Azambuja
Published: January 2025

The discovery of novel cytotoxic drugs is of paramount importance in contemporary medical research, particularly in the search for treatments with fewer side effects and higher specificity. Antimicrobial peptides are an interesting class of molecules for this endeavor. In this context, the LyeTx III, a new peptide extracted from the venom of the Lycosa erythrognatha spider, stands out. The peptide exhibits typical antimicrobial traits: a positive net charge and amphipathic α -helix structure in lipid-like environments. Its unique sequence (GKAMKAIAKFLGR-NH2), identified via mass spectrometry and Edman degradation, shows limited similarity to existing peptides. Significantly, when liposome-encapsulated, LyeTx III demonstrates selective activity against tumor cells in culture. Our MTT results showed that the cytotoxicity of the peptide increased against HN13 cells when administered as liposomes, with their viability in HN13 cells alone being 98%, compared to 38% in liposome-encapsulated form. This finding underscores that the LyeTx III peptide may be a good candidate for the development of new drugs against cancer. Its activity when encapsulated is promising, as it can increase its half-life in the body and can also be targeted to specific tumors.
Artificial Light at Night (ALAN) as an Emerging Urban Stressor for Tree Phenology and Physiology: A Review
Authors: Friulla Luisa , Varone Laura
Published: January 2025

Artificial light at night (ALAN) is an expanding environmental issue, particularly in urban areas. This review aimed to present the state of the art regarding the impact of ALAN on specific and interrelated aspects related to physiological processes and life cycle events in tree species. The reviewed studies highlighted the multifaceted effects of artificial light on plants, offering insights and perspectives to guide future research in this evolving and stimulating field. ALAN disrupts circadian rhythms, alters photoperiodic responses, and affects photosynthesis and carbohydrate metabolism. Changes in phenology such as delayed senescence and altered budburst timing demonstrated species-specific responses, often compounded by other urban stressors like heat and drought. Despite an increased interest, knowledge gaps remain concerning the species-specific responses and the effects of light spectra as well as the long-term consequences on tree physiology. These gaps highlight the need for integrated research approaches and urban planning strategies to mitigate ALAN effects, ensuring the resilience of urban trees and preserving ecosystem services in the context of growing urbanization and climate change.
Truncated NS1 Influenza A Virus Induces a Robust Antigen-Specific Tissue-Resident T-Cell Response and Promotes Inducible Bronchus-Associated Lymphoid Tissue Formation in Mice
Authors: Shurygina Anna-Polina , Shuklina Marina , Ozhereleva Olga , Romanovskaya-Romanko Ekaterina , Kovaleva Sofia , Egorov Andrej , Lioznov Dmitry , Stukova Marina
Published: January 2025

Background: Influenza viruses with truncated NS1 proteins show promise as viral vectors and candidates for mucosal universal influenza vaccines. These mutant NS1 viruses, which lack the N-terminal half of the NS1 protein (124 a.a.), are unable to antagonise the innate immune response. This creates a self-adjuvant effect enhancing heterologous protection by inducing a robust CD8+ T-cell response together with immunoregulatory mechanisms. However, the effects of NS1 modifications on T-follicular helper (Tfh) and B-cell responses remain less understood. Methods: C57bl/6 mice were immunised intranasally with 10 μL of either an influenza virus containing a truncated NS1 protein (PR8/NS124), a cold-adapted influenza virus with a full-length NS1 (caPR8/NSfull), or a wild-type virus (PR8/NSfull). Immune responses were assessed on days 8 and 28 post-immunisation by flow cytometry, ELISA, and HAI assay. Results: In this study, we demonstrate that intranasal immunisation with PR8/NS124 significantly increases tissue-resident CD4+ and CD8+ T cells in the lungs and activates Tfh cells in regional lymph nodes as early as day 8 post-immunisation. These effects are not observed in mice immunised with caPR8/NSfull or PR8/NSfull. Notably, PR8/NS124 immunisation also leads to the development of inducible bronchus-associated lymphoid tissue (iBALT) in the lungs by day 28, characterised by the presence of antigen-specific Tfh cells and GL7+Fas+ germinal centre B cells. Conclusions: Our findings further underscore the potential of NS1-truncated influenza viruses to drive robust mucosal immune responses and enhance vaccine efficacy.
Genetically Engineered Bacterial Ghosts as Vaccine Candidates Against Klebsiella pneumoniae Infection
Authors: Dentovskaya Svetlana V. , Vagaiskaya Anastasia S. , Trunyakova Alexandra S. , Kartseva Alena S. , Ivashchenko Tatiana A. , Gerasimov Vladimir N. , Platonov Mikhail E. , Firstova Victoria V. , Anisimov Andrey P.
Published: January 2025

Background/Objectives Bacterial ghosts (BGs), non-living empty envelopes of bacteria, are produced either through genetic engineering or chemical treatment of bacteria, retaining the shape of their parent cells. BGs are considered vaccine candidates, promising delivery systems, and vaccine adjuvants. The practical use of BGs in vaccine development for humans is limited because of concerns about the preservation of viable bacteria in BGs. Methods: To increase the efficiency of Klebsiella pneumoniae BG formation and, accordingly, to ensure maximum killing of bacteria, we exploited previously designed plasmids with the lysis gene E from bacteriophage φX174 or with holin–endolysin systems of λ or L-413C phages. Previously, this kit made it possible to generate bacterial cells of Yersinia pestis with varying degrees of hydrolysis and variable protective activity. Results: In the current study, we showed that co-expression of the holin and endolysin genes from the L-413C phage elicited more rapid and efficient K. pneumoniae lysis than lysis mediated by only single gene E or the low functioning holin–endolysin system of λ phage. The introduction of alternative lysing factors into K. pneumoniae cells instead of the E protein leads to the loss of the murein skeleton. The resulting frameless cell envelops are more reminiscent of bacterial sacs or bacterial skins than BGs. Although such structures are less naive than classical bacterial ghosts, they provide effective protection against infection by a hypervirulent strain of K. pneumoniae and can be recommended as candidate vaccines. For our vaccine candidate generated using the O1:K2 hypervirulent K. pneumoniae strain, both safety and immunogenicity aspects were evaluated. Humoral and cellular immune responses were significantly increased in mice that were intraperitoneally immunized compared with subcutaneously vaccinated animals (p < 0.05). Conclusions: Therefore, this study presents novel perspectives for future research on K. pneumoniae ghost vaccines.
Enhancing Groundwater Resource Management in the Milan Urban Area Through a Robust Stratigraphic Framework and Numerical Modeling
Authors: Alberti Luca , Mazzon Pietro , Colombo Loris , Cantone Martino , Antelmi Matteo , Marelli Fabio , Gattinoni Paola
Published: January 2025

Groundwater is a critical freshwater resource in Italy’s Po plain, which includes Milan (northern Italy), one of Europe’s most industrialized and urbanized areas. This region relies heavily on groundwater for both industrial and public water supplies. However, the quantity and quality of this resource are vulnerable to both natural and human-induced factors, such as climate change, industrial activities, and changing water use practices. This study investigates and addresses the complex management challenges of groundwater resources of Milan in the framework of the EU directives. A steady-state groundwater flow model was developed as part of the broader project MODEL-MI to aid in the creation of a Water Safety Plan (WSP). This study highlights the importance of accurate stratigraphic data to constructing a reliable hydrogeological conceptual model. The model, calibrated using extensive data, successfully reproduces groundwater flow patterns and will be used both to support decision-making for sustainable groundwater management and to predict future impacts of climate change on water resources.
Landslide Susceptibility Mapping Using an LSTM Model with Feature-Selecting for the Yangtze River Basin in China
Authors: Zuo Peng , Zhao Wen , Yan Wenjun , Jin Jiming , Yan Chaoying , Wu Biqiong , Shao Xiangyu , Wang Weijie , Zhou Zeyu , Wang Jin
Published: January 2025

Landslide susceptibility mapping (LSM) is crucial for disaster prevention in large, complex regions characterized by high-dimensional data. This study proposes a Feature-Selecting Long Short-Term Memory (FS-LSTM) framework to enhance LSM accuracy by integrating feature selection techniques with sequence-based modeling. The Mean Decrease Impurity (MDI) and Information Gain Ratio (IGR) were used to rank landslide conditioning factors (LCFs), and these rankings structured FS-LSTM inputs to assess the impact of feature ordering on model performance. Feature-ordering experiments demonstrated that structured rankings significantly improve model accuracy compared to randomized inputs. Our model outperformed traditional machine learning algorithms, such as logistic regression and Support Vector Machine, as well as standard deep learning models like CNN and basic LSTM, achieving a score of 0.988. The MDI and IGR rankings consistently identified soil type, elevation, and average annual cumulated rainfall as the most influential LCFs, improving the interpretability of the results. Applied to the Yangtze River Basin, the FS-LSTM framework effectively identified landslide-prone areas, aligning with known geological patterns. These findings highlight the potential of combining feature selection with sequence-sensitive deep learning to enhance the robustness and interpretability of LSM. Future studies could expand this approach to other regions and incorporate real-time monitoring systems for dynamic disaster management.
Driving Factors and Variability of Cyanobacterial Blooms in Qionghai Lake, Yunnan–Guizhou Plateau, China
Authors: Dong Yanzhen , Tian Zebin , Li Xiaoyan , Xu Dayong , Zheng Binghui
Published: January 2025

Qionghai Lake is an important freshwater source in the Yunnan–Guizhou Plateau. However, cyanobacterial blooms have been observed recently in Qionghai Lake, but their formation mechanism and control management are not well understood. Herein, phytoplankton, zooplankton, eutrophication, nutrients, and biochemical indices were measured in Qionghai Lake from May 2022 to April 2023. The results showed that cyanobacterial blooms in Qionghai Lake predominated in Anabaena sp. with a density of 1.11 × 107–18.87 × 107 cells/L. Anabaena blooms started in the northwestern area of Qionghai Lake in November 2022 and then expanded to the entire lake until it peaked and subsided in February 2023. Protozoa dominated in zooplankton while having no significant relationship with Anabaena blooms in Qionghai Lake. The trophic level index and chlorophyll a showed similar spatiotemporal trends with Anabaena sp. density, and water quality in the northwest of the Qionghai Lake was worse than in other parts. Total nitrogen (TN) and total phosphorus (TP) were 0.41–0.54 and 0.021–0.045 mg/L from November 2022 to February 2023. TN and TP were positively correlated with Anabaena sp. density, but TP was the most significant environmental factor affecting Anabaena bloom in Qionghai Lake. These findings might provide essential information for improving bloom control and water quality remediation in Qionghai Lake.
Study on Slope Stability of Paleo-Clay Strength Degradation Under Soaking and Wet–Dry Cycles
Authors: Chen Qian , Yan Echuan , Huang Shaoping , Chen Nuo , Xu Hewei , Chen Fengyang
Published: January 2025

Due to Paleo-clay’s unique properties and widespread distribution throughout China, it is essential in geotechnical engineering. Rainfall frequently causes the deformation of Paleo-clay slopes, making slope instability prediction crucial for disaster prevention. This study explored Paleo-clay’s strength degradation and slope stability under soaking and wet–dry cycles. Using Mohr–Coulomb failure envelopes from experiments, curve fitting was used to find the patterns of Paleo-clay strength degradation. Finite element simulations and the strength discounting method were used to analyze the stability and deformation of Paleo-clay slopes. The results indicate that wet–dry cycles impact them more than soaking. Paleo-clay’s cohesion decreases exponentially as the number of wet–dry cycles and soaking times rise, but the internal friction angle changes very little. After 10 wet–dry cycles and 24 days of soaking, iron-bearing clay’s cohesion decreased to 17% and 44% and reticular clay’s to 32% and 48%. Based on the study area characteristics, three slope types were constructed. Their stability exhibited exponential decay. Under soaking, stability remained above 1.4; under wet–dry cycles, type I and II stability fell below 1.0, leading to deformation and failure. All types showed traction landslides with sliding zones transitioning from deep to shallow. Practical engineering should focus on the shallow failures of Paleo-clay slopes.
A Water Quality Prediction Model Based on Modal Decomposition and Hybrid Deep Learning Models
Authors: Zhao Shuo , Liu Ruru , Liu Yahui , Zeng Tao , Chen Chunpeng , Xu Liping
Published: January 2025

When the total nitrogen content in water sources exceeds the standard, it can promote the rapid proliferation of algae and other plankton, leading to eutrophication of the water body and also causing damage to the ecological environment of the water source area. Therefore, making timely and accurate predictions of water quality at the source is of vital importance. Since water quality data exhibit non-stationary characteristics, predicting them is quite challenging. This study proposes a novel hybrid deep learning model based on modal decomposition, ERSCB (EMD-RBMO-SVMD-CNN-BiGRU), to enhance the accuracy of water quality forecasting. The model first employs Empirical Mode Decomposition (EMD) technology to decompose the original water quality data. Subsequently, it quantifies the complexity of the subsequences obtained from EMD using Sample Entropy (SE) and further decomposes the most complex subsequences using Sequential Variational Mode Decomposition (SVMD). To address the matter of selecting balanced parameters in SVMD, this study introduces the Red-Billed Blue Magpie Optimization (RBMO) algorithm to optimize the hyperparameters of SVMD. On this basis, a forecasting model is constructed by integrating Convolutional Neural Networks (CNN) and Bidirectional Gated Recurrent Unit (BiGRU) networks. The experimental results show that, compared to existing water quality prediction models, the ERSCB model has an improved prediction accuracy of 4.0% and 3.1% for the KaShi River and GongNaiSi River areas, respectively.
Environmental Management and Decarbonization Nexus: A Pathway to the Energy Sector’s Sustainable Futures
Authors: Mohamed Abdel-Mohsen O. , Mohamed Dina , Fayad Adham , Al Nahyan Moza T.
Published: January 2025

This paper examines the complex interplay between environmental management (EM) and decarbonization, highlighting how these domains can be seamlessly integrated to create a comprehensive framework for sustainable futures in the energy sector. The framework emphasizes the adoption of green technologies, energy efficiency measures, and innovative carbon capture, utilization, and storage (CCUS) technologies and infrastructures. Central to this approach are circular economy principles, low-greenhouse gas (GHG) emissions production processes, and CCUS strategies. A conceptual model of the EM–decarbonization nexus, comprising six enablers, was developed and illustrated with practical examples from various countries and regions worldwide. The findings reveal significant progress in advancing EM and decarbonization efforts. However, additional support from governments and the private sector is imperative in areas such as research and development, equitable transfer of renewable energy technologies, infrastructure for energy transitions, energy storage systems, green financing mechanisms, public education and community outreach, public–private partnerships, international cooperation, active engagement in global organizations, and the deployment of digital solutions. By addressing these areas, a sustainable future for the energy sector can be realized.
Students’ conceptual understanding in analytic geometry of planes based on their prior mathematical ability
Authors: Negara Habibi Ratu Perwira , Santosa Farah Heniati , Fatimah Ade Evi , Nasrullah Ahmad
Published: January 2025

Mathematical conceptual understanding is a fundamental skill that serves as a foundation for more advanced abilities, including reasoning, communication, connections, and problem-solving. However, this foundational skill is influenced by students’ prior mathematical abilities. Therefore, the objective of this study is to identify and describe differences in students’ mathematical conceptual understanding based on their prior mathematical abilities. This research employs a mixed-method approach, involving 87 purposively selected students enrolled in the Analytic Geometry in Planes and Space course. The research instruments include a mathematical conceptual understanding test and documentation of students’ prior mathematical abilities. Data were analyzed quantitatively using one-way ANOVA and qualitatively by exploring mathematical conceptual understanding across categories of prior mathematical abilities. The findings reveal that both quantitative and qualitative analyses indicate that students with high prior mathematical abilities demonstrate superior mathematical conceptual understanding compared to those with medium or low prior mathematical abilities.
Learning obstacle instrument analysis of proportion concept with praxiology framework
Authors: Maudy Septiani Yugni , Ruli Redo Martila
Published: January 2025

This study explores the development and application of a praxiology-based instrument designed to identify and address learning obstacles in the teaching of the concept of proportion in early algebra. Proportion plays a crucial role in connecting concrete numerical concepts with abstract algebraic thinking; however, many students face significant challenges when transitioning from numerical to algebraic representations. The study utilizes a praxiology framework, which emphasizes the relationship between the type of mathematical task, the techniques employed by students, and the underlying theoretical principles that shape students' understanding. This framework provides a deeper understanding of how task design can influence students' mathematical practices, making it particularly effective for diagnosing learning obstacles in proportion-related tasks. The instrument, which was applied to seventh-grade students in Bandung, Indonesia, consists of five types of tasks aimed at developing students’ skills in arithmetic-algebraic representations and solving linear equations in both abstract and contextual forms. By predicting students' potential solutions and analyzing their problem-solving strategies, the study highlights how the praxiological approach facilitates the identification of key difficulties in students' understanding of proportion. The findings demonstrate that this approach not only helps to diagnose learning obstacles more effectively but also supports the creation of targeted instructional strategies that improve students’ grasp of proportional reasoning. This research contributes valuable insights into the use of praxiology in mathematics education, offering a robust framework for analyzing and overcoming learning obstacles in early algebra instruction.
Utilizing Peer Instruction to Enhance Academic Achievement and Active Learning in Business Education
Authors: Zendrato Rotua , Chang Ben , Fernando Agus
Published: January 2025

Researchers are increasingly interested in evaluating and reshaping traditional teaching practices to implement more student-centered and active learning approaches in higher education. Peer Instruction (PI) has been recognized as an interactive teaching method that significantly impacts student learning by encouraging active participation in an engaging learning environment. This study examines the impact of Peer Instruction (PI) on improving academic performance and active learning in business education beyond its usual limits of application in scientific and numerical fields. This study compared the outcomes of students who engaged in PI with students who took traditional lecture-based classes in business courses. This research uses a quasi-experimental research design because it is not feasible to use a full experimental design because it is impossible to randomly select subjects.
Empirical data, collected through pre-and post-tests, discussion prompts, and PI activities, demonstrated significant improvements in student engagement, cognitive processing, and performance in the PI group compared to the control group. Students who participate in PI report higher test scores and levels of engagement, underscoring PI's potential to foster deeper understanding, critical thinking, and active engagement.
Despite the positive results, the study noted limitations such as a narrow focus on the class by one instructor and the absence of marked differences in conceptual understanding between the PI and individual study groups, then only tested academic achievement without engaging students' levels of critical thinking. Highlighting the effectiveness of PI in business education, this research calls for broader application and further investigation into the role of PI in enhancing active learning, suggesting future exploration into diverse academic areas, methodologies, and technological tools, as well as applying it to examine critical thinking and interaction students to deeper learning content.
Developing and Facilitating a Workplace Communication Workshop for Engineering Student Interns: Implications for Practice
Authors: Rahimi Muhammad , Blackstone Brad
Published: January 2025

In this paper, Engeström’s third-generation activity theory (AT; 2001) is adopted as an analytic tool to analyze a workplace communication workshop for engineering students and an experienced educator’s cognition and practices. Curricular elements of the workshop and the educator’s pedagogical approach are analyzed together with the motivation for a specific learning experience design and the rationale for adopting such practices. AT served as an invaluable analytic lens for our reflection on the workshop’s design, its activities, and the educator’s cognition and practices. This reflection provides a worked sample for AT-based reflective practice and strategies for developing workplace communication workshops. It is concluded that by using AT as an analytic tool for reflection, educators can effectively reflect upon and analyze their course design and teaching practices, thereby externalizing their knowledge, skills, and attitudes. Educators can develop their expertise through such a reflective process and create more engaging and effective courses. We also recommend that AT be adopted as an analytic tool in reflective practice modules in communication teacher education and training programs to enable prospective and novice teachers to engage in reflective practice and purposefully develop their teaching expertise throughout their careers.
Aphra Behn’s use of translatio: Mediation, adaptation, and emulation in a cross-channel perspective
Authors: Cottegnies Line
Published: January 2025

Recent historians of fiction have shown that the “British” novel was essentially a transnational phenomenon in the Restoration. French was the dominant source language for literary translation as a whole in the Restoration period, and translations played a prominent role in the development of a national literature. Aphra Behn, whose role as a translator and adaptor of French texts is now recognized, offers a perfect vantage point from which to measure the multifaceted impact of French literature on seventeenth-century English literature. The sheer range of her strategies as a translator is extraordinary as she explores all the shades between literal paraphrase and free imitation. This article argues that far from being merely commercial her translations form a coherent body of works which manifests a form of emulation with their originals that is fully creative.
THE EFFECT OF DEBT TO ASSET RATIO, CURRENT RATIO AND SIZE ON EARNING PER SHARE: MEDIATION OF RETURN ON ASSET
Authors: Rivai Yutiandry , Angelina Vanessa , Hafni Layla , Miran Ikas , Prihastuti Asepma Hygi
Published: January 2025

Tujuan dalam penelitian ini adalah untuk mengetahui dan menganalisis pengaruh Debt to Asset Ratio, Current Ratio dan ukuran perusahaan terhadap Return on Assets dan Earning Per Share. Penelitian dilakukan pada Perusahaan Sektor industri barang konsumsi selama Periode 2016-2020 yang terdaftar di Bursa Efek Indonesia (BEI). Populasi dalam penelitian ini adalah seluruh perusahaan consumer goods yang terdaftar di BEI sampai 2020 yang berjumlah 61 perusahaan, metode penentuan sampel dengan teknik purposive sampling. Sehingga menjadi populasi dalam penelitian ini adalah seluruh perusahaan consumer goods yang terdaftar di BEI sampai 2020 yang berjumlah 61 perusahaan. Analisis data menggunakan metode regresi linier berganda. Hasil penelitian menjelaskan bahwa Debt to Assets Ratio memiliki pengaruh positif dan tidak signifikan, sementara Current Ratio memiliki pengaruh positif dan signifikan dan ukuran perusahaan memiliki pengaruh negatif dan signifikan terhadap Return on Assets. Sedangkan Debt to Assets Ratio dan Current Ratio memiliki pengaruh negatif dan tidak signifikan, sementara ukuran perusahaan dan Return on Assets memiliki pengaruh positif dan signifikan terhadap Earning Per Share. Secara tidak langsung Debt to Assets Ratio, Current Ratio, dan ukuran perusahaan tidak berpengaruh terhadap Earning Per Share melalui Return on Assets.
 
The purpose of this study is to determine and analyze the effect of Debt to Asset Ratio, Current Ratio and company size on Return on Assets and Earning Per Share. The study was conducted on Consumer Goods Industry Sector Companies during the 2016-2020 Period listed on the Indonesia Stock Exchange (IDX). The population in this study were all consumer goods companies listed on the IDX until 2020, totaling 61 companies, the sampling method used was purposive sampling technique. So that the population in this study was all consumer goods companies listed on the IDX until 2020, totaling 61 companies. Data analysis used multiple linear regression methods. The results of the study explain that Debt to Assets Ratio has a positive and insignificant influence, while Current Ratio has a positive and significant influence and company size has a negative and significant influence on Return on Assets. Whereas Debt to Assets Ratio and Current Ratio have a negative and insignificant effect, while company size and Return on Assets have a positive and significant effect on Earning Per Share. Indirectly, Debt to Assets Ratio, Current Ratio, and company size do not affect Earning Per Share through Return on Assets.