bluuebunny/crossref_metadata_2025 huggingface dataset:
Mode Heterogeneous Multimode Power Splitter Based on Cascaded Mode-Dependent Splitters and Converters
Authors: Xu Xin , Chen Hongliang , Fu Xin , Yang Lin
Published: May 2024

To the best of our knowledge, a novel concept of mode heterogeneity for the design of multimode devices is presented in this paper and applied to the design of scalable multimode power splitters. Based on a cascade of mode-dependent splitters and converters, we achieve beam splitting and mode conversion for four modes from TE0 to TE3 in the bandwidth from 1525 nm to 1560 nm. The measurements of the device at 1550 nm show excellent performance, with the insertion loss ranging from 0.16 dB to 0.63 dB, crosstalk all below −16.71 dB, and power uniformity between 0.026 dB and 0.168 dB.
Trophoblast Cell Surface Antigen 2 (Trop2) Is Expressed in Cases of EBV-Positive Diffuse Large B-Cell Lymphoma Emerging from Angioimmunoblastic T-Cell Lymphoma
Authors: Ghandili Susanne , Dierlamm Judith , Bokemeyer Carsten , von Bargen Clara Marie , Menz Anne , Weidemann Sören Alexander
Published: May 2024

Although trophoblast cell surface antigen 2 (Trop2)-targeting drugs are already approved or under investigation in various solid tumors, the significance of Trop2 in lymphoma is unknown. Thus, our objective was to investigate the expression of Trop2 in diffuse large B-cell lymphoma (DLBCL) through a systemic immunohistochemistry screening. We constructed a tissue microarray comprising tissue from 92 DLBCL patients, each diagnosed at the University Medical Center Hamburg-Eppendorf (2020–2022). Trop2-immunohistochemistry was carried out, and positive staining was deemed a specific membranous positivity. Four samples were derived from Epstein-Barr virus (EBV)-positive DLBCL, with one case of EBV-positive DLBCL following angioimmunoblastic T-cell lymphoma (AITL). Strong Trop2 immunostaining was detectable in 1 of 91 analyzable samples, originating from a patient with a composite EBV-positive DLBCL emerging from AITL. Therefore, we performed an additional database search to identify all cases of composite EBV-positive DLBCL emerging from AITL since 2015. Five additional cases were identified and stained for Trop2, revealing two cases with strong B-blast positivity. Our preliminary data imply that Trop2 appears absent in de novo DLBCL, whereas Trop2 is strongly expressed in cases of a rare variant of EBV-positive DLBCL. Further investigations are needed to confirm our results, particularly on the subset of EBV-positive DLBCL emerging from AITL.
A Snow Water Equivalent Retrieval Framework Coupling 1D Hydrology and Passive Microwave Radiative Transfer Models
Authors: Cao Yuanhao , Luo Chunzeng , Tan Shurun , Kang Do-Hyuk , Fang Yiwen , Pan Jinmei
Published: May 2024

The retrieval of continuous snow water equivalent (SWE) directly from passive microwave observations is hampered by ambiguity, which can potentially be mitigated by incorporating knowledge on snow hydrological processes. In this paper, we present a data assimilation (DA)-based SWE retrieval framework coupling the QCA-Mie scattering (DMRT-QMS) model (a dense medium radiative transfer (RT) microwave scattering model) and a one-dimensional column-based multiple-layer snow hydrology model. The snow hydrology model provides realistic estimates of the snowpack physical parameters required to drive the DMRT-QMS model. This paper devises a strategy to specify those internal parameters in the snow hydrology and RT models that lack observational records. The modeled snow depth is updated by assimilating brightness temperatures (Tbs) from the X, Ku, and Ka bands using an ensemble Kalman filter (EnKF). The updated snow depth is then used to predict the SWE. The proposed framework was tested using the European Space Agency’s Nordic Snow Radar Experiment (ESA NoSREx) dataset for a snow field experiment from 2009 to 2012 in Sodankylä, Finland. The achieved SWE retrieval root mean square error of 34.31 mm meets the requirements of NASA and ESA snow missions and is about 70% less than the open-loop SWE. In summary, this paper introduces a novel SWE retrieval framework that leverages the combined strengths of a snow hydrology model and a radiative transfer model. This approach ensures physically realistic retrievals of snow depth and SWE. We investigated the impact of various factors on the framework’s performance, including observation time intervals and combinations of microwave observation channels. Our results demonstrate that a one-week observation interval achieves acceptable retrieval accuracy. Furthermore, the use of multi-channel and multi-polarization Tbs is preferred for optimal SWE retrieval performance.
Planning for Adaptation? Examining the Planning Integration for Hazard Risk Reduction
Authors: Wu Yiwen , Lyles Ward , Overstreet Kelly , Sutley Elaina
Published: May 2024

Integrated planning—including multiple planning practices for common purposes—is deemed essential for bringing stakeholders together for effective hazard risk reduction. Scholarly attempts to examine if and how distinct plans and planning processes are integrated have ebbed and flowed over time, with a recent resurgence in attention. Utilizing tools from network science, we analyzed four types of planning practices and uncovered considerable variations across local hazard risk-reduction support networks. Our findings reveal that certain communities relied heavily on a few critical actors for risk reduction, making them vulnerable to institutional turbulence. In turn, we point to growing needs for far-reaching and overlapping networks. Our study adds to the literature by integrating multiple planning practices to support more concerted local efforts in hazard risk reduction.
A Comparative Analysis of Advanced Machine Learning Techniques for River Streamflow Time-Series Forecasting
Authors: Abdoulhalik Antoifi , Ahmed Ashraf A.
Published: May 2024

This study examines the contribution of rainfall data (RF) in improving the streamflow-forecasting accuracy of advanced machine learning (ML) models in the Syr Darya River Basin. Different sets of scenarios included rainfall data from different weather stations located in various geographical locations with respect to the flow monitoring station. Long short-term memory (LSTM)-based models were used to examine the contribution of rainfall data on streamflow-forecasting performance by investigating five scenarios whereby RF data from different weather stations were incorporated depending on their geographical positions. Specifically, the All-RF scenario included all rainfall data collected at 11 stations; Upstream-RF (Up-RF) and Downstream-RF (Down-RF) included only the rainfall data measured upstream and downstream of the streamflow-measuring station; Pearson-RF (P-RF) only included the rainfall data exhibiting the highest level of correlation with the streamflow data, and the Flow-only (FO) scenario included streamflow data. The evaluation metrics used to quantitively assess the performance of the models included the RMSE, MAE, and the coefficient of determination, R2. Both ML models performed best in the FO scenario, which shows that the diversity of input features (hydrological and meteorological data) did not improve the predictive accuracy regardless of the positions of the weather stations. The results show that the P-RF scenarios yielded better prediction accuracy compared to all the other scenarios including rainfall data, which suggests that only rainfall data upstream of the flow monitoring station tend to make a positive contribution to the model’s forecasting performance. The findings evidence the suitability of simple monolayer LSTM-based networks with only streamflow data as input features for high-performance and budget-wise river flow forecast applications while minimizing data processing time.
Spatiotemporal Patterns and Driving Factors of Green and Low-Carbon Urbanization in the Yangtze River Delta Region, China
Authors: Huang Yingao , Kuai Chenjun , Wang Feier
Published: May 2024

Green and low-carbon urbanization (GLCU) is as a key objective within the realm of urban sustainable development. The extent of coordination between urbanization and low-carbon development determines the level of GLCU. However, the complex driving mechanism of GLCU has not garnered the required attention within the existing literature. In light of this, the present paper introduces a multi-dimensional comprehensive evaluation framework aimed at assessing the level of GLCU. Specifically, it delves into the spatial–temporal characteristics and driving forces that underpin GLCU. The results indicate that the level of GLCU in the YRD region increased rapidly from 2005 to 2020, evolving from low coordination to moderate coordination. Yet, the trade-off between urbanization and low-carbon development still exists. The surge in population density and economic prosperity emerged as the principal positive drivers of GLCU, while the carbon emissions intensity exerted a negative influence. Furthermore, the effect of industrial structure shifted from a positive driver to a negative one. The effects of these drivers upon GLCU varied at different urbanization stages and determined the patterns of urban development, indicating that policies for sustainable development should be tailored to cities at different urbanization stages. These findings can provide useful information for policy makers and urban planners in managing and promoting urban sustainable development.
The Use of Cultural Landscape Fragmentation for Rural Tourism Development in the Zemplín Geopark, Slovakia
Authors: Rybárová Jana , Rybár Radim , Tometzová Dana , Wittenberger Gabriel
Published: May 2024

This study outlines the creation of hiking routes in Slovakia’s cultural landscape, focusing on regions with marginal interest, low tourism engagement, and predominant monocultural blocks. The methodology was systematically applied to the Zemplín Geopark in eastern Slovakia, drawing upon historical cartographic records from the Josephine mapping period (1764–1787) to the present day. The investigation identified and delineated 14 hiking trails, offering historical and tourism significance while promoting multifunctionality. Our research introduces sustainable development avenues for regions with marginal interest, providing ecological and tourist benefits that enhance the overall quality of life. The findings align with the Common Agricultural Policy’s objectives for 2021–2027, addressing challenges related to large-scale field fragmentation. Two identified obstacles include property-legal challenges and issues arising from inadequate map registration, which current methods, unfortunately, fail to address.
Data-Driven Approach for Selecting Mechanical Rebar Couplers Based on the Shape and Structural Characteristics of Reinforcing Bars for Sustainable Built Environment
Authors: Lim Jeeyoung , Kim Sunkuk
Published: May 2024

Lap splices are the most commonly used method worldwide because they do not require specific equipment or skilled workers. However, lap splices incur high construction costs because of the long splice lengths required for large-diameter rebars in megastructures, as well as issues pertaining to material supply, labor costs, constructability, and project duration. Additionally, approximately 15% more rebar is required because of the overlap. Energy saving for a sustainable built environment is possible if the disadvantage of lap splices, which generate high CO2 emissions due to the excessive use of rebar, are resolved. Hence, mechanical rebar couplers (MRCs) have been developed. However, despite their advantages, they have not been widely applied in construction sites owing to concerns regarding safety, quality, and constructability. This is because data on MRC, including maintenance, and environmental impact, are not organized, making it difficult to select a coupler suitable for the environment during the construction stage. Therefore, a data-driven approach for selecting MRCs based on the reinforcing bar shape and structural characteristics is proposed in this study. The T-epoxy filled sleeve coupler was found to be the best in terms of seismic performance, durability, corrosion resistance, and long-term performance. In addition, using a data-driven MRC selection algorithm using the T-threaded coupler for one rebar over two floors resulted in 56% more efficient labor productivity, 15% shorter assembly time, 17% lower costs, and 26% lower CO2 emission. Using a developed algorithm, the appropriate MRC can easily and rapidly be selected for frequent design changes.
Root System Evolution Survey in a Multi-Approach Method for SWBE Monitoring: A Case Study in Tuscany (Italy)
Authors: Giachi Emanuele , Giambastiani Yamuna , Giannetti Francesca , Dani Andrea , Preti Federico
Published: May 2024

Land degradation and soil erosion, intensified by frequent intense hydro-meteorological events, pose significant threats to ecological processes. In response to the environmental challenges, there is a growing emphasis on employing Nature-Based Solutions (NBS), such as Soil and Water Bioengineering (SWBE) techniques, which promote a sustainable approach and materials for the restoration of natural areas damaged by climate events, unlike traditional “grey” engineering works. However, the effective implementation of SWBE interventions requires a multidisciplinary monitoring approach, considering engineering, geological, ecological, biological, and landscape aspects. The success of these interventions depends on evaluating both short-term stabilities provided by the non-living supporting structure and the long-term development of vegetation introduced during the work. Monitoring should regard structural integrity assessments, vegetation evolution studies, and analyses of root system efficiency (distribution, mechanical characteristics, etc.). This study wants to fill the research gap in SWBE management by proposing a comparison of two study techniques for a root system development evaluation, within a multi-approach methodology for the assessment of these interventions in terms of soil stability and natural evolution. The paper provides insights into geotechnical analysis within a shallow landslide, comparing two different methods for the evaluation of root system evolution. Direct methods (RAR) and indirect methods (ERT) were used for root development monitoring and then compared. Vegetation development was assessed by NDVI parameter by analysing Landsat satellite images. An overall analysis of the data obtained from monitoring the study area shows good plant development, thanks to the SWBE intervention, which in addition to the slope stability effect contributes to better water regulation and initiates a natural ecological succession. The findings contribute to advancing the understanding of the effectiveness of SWBE techniques, offering valuable information for future bioengineering projects and environmental conservation efforts, and promoting them as sustainable techniques for natural recovery.
Enhancing Corporate Sustainability through Just-In-Time (JIT) Practices: A Meta-Analytic Examination of Financial Performance Outcomes
Authors: García-Cutrín Javier , Rodríguez-García Carlos
Published: May 2024

This paper utilizes a meta-analytic approach to examine the correlation between Just-In-Time (JIT) practices and financial performance. The investigation assesses JIT’s influence on key financial metrics, including Return on Investment (ROI), Return on Sales (ROS), Asset Turnover, and Profit Margins. Results indicate a robust positive correlation between JIT implementation and enhanced financial outcomes, demonstrating that JIT significantly contributes to both operational efficiency and financial health. The findings illustrate that JIT’s effectiveness varies by organizational scale and economic context, with larger firms and stable economic conditions seeing the most pronounced benefits. Conversely, smaller firms might face challenges in harnessing JIT’s full financial potential, underscoring the importance of tailored implementation strategies. This study confirms the strategic value of JIT for boosting profitability and efficiency, providing managers with actionable insights to optimize JIT deployment. It also suggests areas for future research to refine understanding of JIT’s variable effects across different operational contexts and explore potential contributions to sustainability initiatives. This contribution enriches the discourse on JIT’s role in enhancing corporate financial performance and opens the door to examining its broader impacts on sustainable business practices.
The Basic Process of Lighting as Key Factor in the Transition towards More Sustainable Urban Environments
Authors: Peña-García Antonio , Castillo-Martínez Agustín , Ernst Sebastian
Published: May 2024

The design of lighting installations on roads and urban infrastructure has strictly followed the regulatory requirements of each country for a long time. Based on the traffic intensity, the presence of pedestrians and the nature of activities within the area, these regulations have been used to establish the luminance or illuminance levels from or on the pavement, the minimum average uniformity, the maximum glare and the minimum energy efficiency. Accurate values of these static parameters are supposed to ensure safety, security, and efficacy, and have traditionally been considered as the main targets of lighting installations. Therefore, compliance with these regulations indicates whether an installation is legal or not. Although this philosophy is operative, the reality is different due to two main issues. First, the progressive ageing of populations, mainly in North America and Europe, the changing circumstances of traffic flow and modalities and the presence of groves or socioeconomic factors, might have a strong impact on the safety, security and sustainability of cities. Secondly, the current regulations leave out perceived safety and security issues, as well as the well-being of people; that is, how people feel about the city independently of real danger. In this research, the Basic Process of Lighting (BPL) is formulated including, for the first time, the human factors involved when people develop their activities under public lighting. Using this framework, the potential factors influencing human wellbeing and feelings are summarized after being rated by people in a survey distributed among 133 participants. The results highlight a higher perceived impact of social factors compared to physical and visual ones.
Students’ Perceptions of Teacher Training for Inclusive and Sustainable Education: From University Classrooms to School Practices
Authors: Garcia-Vallès Xènia , Badia Martín Mar , Gavaldà Josep Maria Sanahuja , Pérez Romero Antonio
Published: May 2024

Teachers are the pillar for the development of inclusion. Hence, their initial training becomes a matter of relevance for the success of creating inclusive schools. This work contributes to the achievement of the Sustainable Development Goal 4: ensure inclusive and equitable quality education and promote lifelong learning opportunities for all. The other objectives were to delimit the competences in inclusive education for teachers and analyse the perception of future teachers in the acquisition of IE competences in the context of university classrooms and internship centres. This research was carried out with 315 students from Catalan public universities through a questionnaire to assess their perception of these competencies. The results show that competences related to leadership in educational environments, inclusive values, or the identification of the students’ abilities are being developed in internship centres. However, the university classroom context lead to the development of competences related to cooperative learning and assessment. In addition, there are significant differences between students who follow specialised teacher training in special needs and those who do not follow it. In conclusion, there is a need to extend specific training to all students and for a greater interrelationship between the training for developing competences in both contexts.
Effect of Treated/Untreated Recycled Aggregate Concrete: Structural Behavior of RC Beams
Authors: Abdo Ayman , El-Zohairy Ayman , Alashker Yasser , Badran Mohamed Abd El-Aziz , Ahmed Sayed
Published: May 2024

Using recycled concrete aggregates from construction and demolition wastes on structural concrete is a sustainable solution to reduce the consumption of natural resources and the detrimental effects of concrete production on the environment. This paper has collected much data from the literature to study fresh, mechanical properties and durability of concrete made of treated/untreated recycled aggregate (RA). Furthermore, the flexural and shear behavior of recycled aggregate concrete (RAC) beams was studied. This study discussed the distinctions and similarities between reinforced RAC beams and reinforced natural aggregate concrete (NAC) beams. The results of this review’s analysis clearly show that reinforced RAC beams with different RAC ratios perform structurally on par with or slightly worse than reinforced NAC beams, demonstrating the viability of RAC for structural applications. Emphasis is placed on carefully choosing and adjusting material models for recycled aggregate concrete. Ultimately, guidelines for future inquiries in this field are delineated and deliberated upon. The review will be advantageous for academics and professionals who aim to acquire a comprehensive comprehension of the behavior of RAC beams. It addresses several practical concerns connected to the numerical modeling of these components, which have not been adequately covered in existing literature.
Culture and Sustainability: Evidence from Tea Culture and Corporate Social Responsibility in China
Authors: Mao Lina , Sun Guangfan , He Yining , Chen Huixia , Guo Changwei
Published: May 2024

We aim to explore the prerequisites for corporate sustainability from the perspective of non-formal institutions such as culture. Specifically, we seek to investigate whether and how Chinese tea culture influences corporate social responsibility (CSR). We have developed an OLS regression model to examine the relationship between tea culture and CSR, and our findings indicate that local tea culture yields positive effects. To address endogeneity concerns related to this correlation, we employed the local geographic slope as an instrumental variable for tea culture. Subsequent research highlights that the female executive, serving as a mediator variable, represents the primary mechanism influenced by tea culture. Furthermore, our study demonstrates that tea culture exerts a more significant impact on small and medium-sized enterprises as well as state-owned enterprises. Overall, this research contributes to the literature on the determinants of CSR from the vantage point of informal institutions, offering a fresh perspective for exploring the economic ramifications of tea culture for both academia and practitioners. Moreover, it furnishes valuable insights for advancing the sustainable development of enterprises.
Ecological–Economical and Ethno-Cultural Determinants of the Development of Organic Farming in Kazakhstan
Authors: Pashkov Sergey V. , Imashev Eduard Z. , Baubekova Gaukhar K. , Kaimuldinova Kulyash D. , Tokpanov Yerkin A. , Nurgaliyeva Gulshat Z. , Baimukasheva Gaini K. , Kenzhebay Rabiga N. , Kassenov Soltanbek K. , Ukrainskiy Pavel A.
Published: May 2024

In the context of the transition to sustainable agriculture in Kazakhstan, the article considers one of its forms—organic farming. The adopted laws and by-laws not only have not contributed to but have also significantly hindered the development of organic farming due to the complexity of their implementation in the Kazakh legal field. The activities of Kazakhstani public organizations, deprived of any state support, are symbolic in nature. The absolute instability of organic production, the multidirectional long-term dynamics of the area of organic land and the cost yield of the products are demonstrated. The lack of demand for organic farming products among the population of Kazakhstan is due to socio-economic determinants, the dominance of livestock products in the nutrition structure of the indigenous population, only a small part of the inhabitants of megacities being the main consumers of any organic products, the exorbitant share of food costs and the high premium of organic products. The reasons for the ecological and economic instability of organic farming are the extensive development model, the lack of subsidiary obligations of the state and the zero-marginal cost of the export product. Conservative, utilitarian and innovative ways of developing organic farming are proposed.
A Review of Smart Materials in 4D Printing for Hygrothermal Rehabilitation: Innovative Insights for Sustainable Building Stock Management
Authors: Farham Babak , Baltazar Luis
Published: May 2024

There is an issue in the building stock, especially in Europe, concerning energy efficiency and climate change adaptation. Due to insufficient thermal insulation and passive solutions, the majority of the existing buildings are not only ill-prepared for the negative effects of climate change, but they also contribute to higher energy consumption. The combination of smart materials and 4D printing for hygrothermal rehabilitation of building facades is the main topic of this review paper. The paper examines the application of smart materials in construction to overcome problems with moisture and heat transfer and other issues in the building envelope. It discusses numerous instances of this printing technology’s applications, such as particular responsive elements, identifies trends and draws attention to knowledge gaps in the field, and assesses environmental and economic impacts. The objective is to offer comparable data to aid in upcoming studies concerning the creation of 4D-printed building façade solutions. Additionally, the paper can be interpreted as a collaborative attempt to influence the direction of future hygrothermal building rehabilitation practices. It also aims to assist designers and other relevant parties in understanding the advantages, restrictions, and difficulties related to 4D printing and smart materials for the sustainable management of buildings.
Using the Theoretical-Experiential Binomial for Educating AI-Literate Students
Authors: Modran Horia Alexandru , Ursuțiu Doru , Samoilă Cornel
Published: May 2024

In the dynamic landscape of modern education, characterized by an increasingly active involvement of IT technologies in learning, the imperative to transfer to university students the skills necessary to integrate Artificial Intelligence (AI) into the process represents an important goal. This paper presents a novel framework for knowledge transfer, diverging from traditional programming language-centric approaches by integrating PSoC 6 microcontroller technology. This framework proposes a cyclical learning cycle encompassing theoretical fundamentals and practical experimentation, fostering AI literacy at the edge. Through a structured combination of theoretical instruction and hands-on experimentation, students develop proficiency in understanding and harnessing AI capabilities. Emphasizing critical thinking, problem-solving, and creativity, this approach equips students with the tools to navigate the complexities of real-world AI applications effectively. By leveraging PSoC 6 as an educational tool, a new generation of individuals is efficiently cultivated with essential AI skills. These individuals are adept at leveraging AI technologies to address societal challenges and drive innovation, thereby contributing to long-term sustainability initiatives. Specific strategies for experiential learning, curriculum recommendations, and the results of knowledge application are presented, aimed at preparing university students to excel in a future where AI will be omnipresent and indispensable.
Weighted Average Ensemble-Based PV Forecasting in a Limited Environment with Missing Data of PV Power
Authors: Lee Dae-Sung , Son Sung-Yong
Published: May 2024

Photovoltaic (PV) power is subject to variability, influenced by factors such as meteorological conditions. This variability introduces uncertainties in forecasting, underscoring the necessity for enhanced forecasting models to support the large-scale integration of PV systems. Moreover, the presence of missing data during the model development process significantly impairs model performance. To address this, it is essential to impute missing data from the collected datasets before advancing with model development. Recent advances in imputation methods, including Multivariate Imputation by Chained Equations (MICEs), K-Nearest Neighbors (KNNs), and Generative Adversarial Imputation Networks (GAINs), have exhibited commendable efficacy. Nonetheless, models derived solely from a single imputation method often exhibit diminished performance under varying weather conditions. Consequently, this study introduces a weighted average ensemble model that combines multiple imputation-based models. This innovative approach adjusts the weights according to “sky status” and evaluates the performance of single-imputation models using criteria such as sky status, root mean square error (RMSE), and mean absolute error (MAE), integrating them into a comprehensive weighted ensemble model. This model demonstrates improved RMSE values, ranging from 74.805 to 74.973, which corresponds to performance enhancements of 3.293–3.799% for KNN and 3.190–4.782% for MICE, thereby affirming its effectiveness in scenarios characterized by missing data.
ARIMA-Driven Vegetable Pricing and Restocking Strategy for Dual Optimization of Freshness and Profitability in Supermarket Perishables
Authors: Li Hongliang , Liu Jun , Qiu Jiangjie , Zhou Yunsen , Zhang Xu , Wang Yuming , Guo Wei
Published: May 2024

In the evolving landscape of perishable goods management, where the balance between minimizing waste and maximizing profitability is paramount, this work introduces an innovative approach to pricing and inventory decisions for products with limited shelf lives, focusing on vegetables in supermarkets. The contribution lies in its integration of an automated pricing and restocking decision model that leverages autoregressive integrated moving average (ARIMA) forecasting techniques alongside dynamic pricing strategies tailored to the goods’ freshness and remaining shelf life. The study uses a comprehensive sales, spoilage rates, and customer demand dataset to apply ARIMA forecasting for optimal restocking and adjusts prices dynamically based on product freshness, promoting competitive pricing and waste reduction. The results demonstrate the model’s effectiveness, reducing spoilage rates by up to 30% and increasing profitability margins by about 15%, highlighting its practical utility in real-world scenarios. The research highlights the potential for supermarkets to improve perishable goods inventory management, leading to significant economic benefits and reduced food waste. This study contributes to sustainable retail practices aligning with global responsible consumption and production initiatives, offering a scalable economic efficiency and environmental stewardship solution.
A Panel Analysis Regarding the Influence of Sustainable Development Indicators on Green Taxes
Authors: Sabău-Popa Claudia Diana , Bele Alexandra Maria , Bucurean Mirela , Mociar-Coroiu Sorina Ioana , Tarcă Naiana Nicoleta
Published: May 2024

Green taxes are taxes collected to protect the environment by controlling the negative effects of certain activities and products on the environment. They are also an instrument of environmental policy and can therefore contribute to several sustainable development goals. According to the studies carried out, the green economy aims to ensure sustainable development. The main objective of this paper is to identify the existing relationships between green taxes and sustainable economic development through a dynamic panel analysis. A dynamic panel analysis was therefore carried out on the existing links between environmental taxes and charges at the European level and the indicators of the circular economy. The results of the two dynamic regressions for the two dependent variables, namely total green taxes and energy taxes, show a positive and significant correlation with the variation of GDP and with primary energy consumption, confirming the hypothesis that environmental taxes and energy taxes are closely linked to these two important indicators of sustainable development. Thus, as GDP changes, the taxes on energy production and the energy products used in both transport and stationary applications increase. As a result of the analysis, we can note that the increase in primary energy consumption and the consumption of raw materials leads to an increase in environmental and energy taxes. Energy taxes are a possible solution to reduce CO2 emissions in third world countries and may even stimulate climate action. In contrast, we found no significant correlation between green taxes and the following variables: Human Development Index, net greenhouse gas emissions, private investment and gross value added related to circular economy sectors, the consumption of raw materials, waste generated, waste treatment, the supply, transformation, and consumption of renewable energy, public expenditure on environmental protection, and climate-related economic losses.
Understanding Romanian Generational Preferences and Travel Decision-Making When Choosing a Rural Destination
Authors: Poruțiu Andra Ramona , Brata Anca Monica , Dumitras Diana E. , Oros Olivia Paula , Muresan Iulia C.
Published: May 2024

The COVID-19 pandemic has significantly altered consumer behavior and reshaped the tourism industry, particularly impacting travel destination choices. Pre-pandemic, travelers prioritized experiences and adventure, often overlooking health and safety concerns. However, during and after the pandemic, health, hygiene, and the COVID-19 situation emerged as crucial factors in choosing a rural destination, alongside economic considerations. The current study analyzed the tourists’ preferences in the North-West development region of Romania when choosing a rural destination. An online survey was conducted, and 563 questionnaires were validated in the end. The principal component analysis used to analyze the collected data led to a two-factor solution: “sanitary and administrative” and “economic and social”. Comparative analysis based on age showed significant differences in education, income, and family composition between Generation Y and Generation Z. Preferences for domestic destinations and participation in festivals were higher among Generation Z, while interest in international travel was comparable between the generations. These findings provide insights into the evolving travel behaviors and preferences of different age groups in the wake of the pandemic.
Multi-Tier Supply Chain Learning Networks: A Simulation Study Based on the Experience-Weighted Attraction (EWA) Model
Authors: Gong Yu , Xu Xiaojiang , Zhao Changping , Schoenherr Tobias
Published: May 2024

Supply chain learning (SCL), which is reflected in organizational learning, referring to the learning between organizations in the supply chain, carries the promise to enable sustainable competitive advantages. Many large multinational companies, such as IKEA, Nestle, and Microsoft, have therefore integrated supply chain knowledge management and continuous learning into their corporate strategies. While there is evidence in extant research about a positive correlation between both the subjective attitude and learning ability of supply chain members and their performance improvement, areas where insight is still missing pertain to the relationship between supply chain members’ subjective psychological factors, and their relationship network structures. This is a serious omission, since these dimensions likely play a key role in the dynamics underlying SCL. In order to alleviate this void, we consider a multi-tier SCL network and develop a model in which a supply chain member’s attraction is weighted based on its previous learning experience. The game mechanism underlying SCL captured in this experience-weighted attraction (EWA) model is then tested using a simulation study of IKEA China’s multi-tier supply chain network for its sustainable cotton initiative. The results suggest that learning costs can be reduced and learning spillover befits can be increased by the provision of rewards to network member companies and better communication. In addition, the perception of and preference for SCL by suppliers can be influenced by initiating sustainable advocacy and providing knowledge and technology training, as well as fostering a range of subjective factors we investigate in our study, such as the strategic attractiveness the decline ratio due to forgetting, the attractiveness improvement ratio due to preferences, and the response sensitivity to strategies. The findings offer insight into the influence mechanisms of the supply chain network structure and subjective attitude about SCL, which are especially applicable to large, multinational enterprises.
Exploring the Impact of Humic Biostimulants on Cassava Yield and Nutrition in Northeast Brazil
Authors: Santos Maisa da Conceição , Cavalcanti Mônica Tejo , Pessoa Larissa Nicácio , Silva Zenaide Gomes da , da Silva Allisson Miguel , Souza Tancredo , Henschel Juliane Maciel , Pereira Emmanuel Moreira , Diniz Neto Manoel Alexandre , Diniz Belísia Lúcia Moreira Toscano
Published: May 2024

Cassava is a staple food mainly produced with low management inputs, causing soil depletion and low yields. The use of organic inputs, such as humic substances (HSs), represents a sustainable alternative to increase cassava growth and production, mainly in semi-arid regions such as the Brazilian Northeast. Thus, the objective was to evaluate the foliar application of a biostimulant based on humic substances on the morphophysiology, production, and mineral nutrient contents of cassava. The biofortified cultivar BRS Dourada was grown under field conditions and foliar application of a biostimulant based on humic substances (BHSs, treated plants) or water (untreated, control). The experiment was conducted in a randomized block design with four repetitions. At 225 days after planting, the growth, productivity, and mineral nutrient contents of soil, roots, and leaves were determined. No differences between treated and untreated plants were found for growth and productivity (average 15.2 t ha−1). On the other hand, BHS treatment reduced net carbon assimilation, water use efficiency, and carboxylation efficiency by 34%, 24%, and 47%, respectively. Moreover, BHS treatment reduced nutrient uptake from soil, and Na and K contents in roots and leaves, respectively. A foliar BHS application is not recommended for cassava production in the conditions evaluated here.
Construction Safety and Efficiency: Integrating Building Information Modeling into Risk Management and Project Execution
Authors: Salzano Antonio , Cascone Stefano , Zitiello Enrico Pasquale , Nicolella Maurizio
Published: May 2024

In the evolving construction landscape, this study introduces a novel methodology leveraging Building Information Modeling (BIM) to revolutionize safety management across diverse projects. By transitioning from traditional, reactive approaches to a proactive, comprehensive framework, BIM’s integration into the design and execution phases enables the dynamic assessment and mitigation of risks, thereby enhancing workplace safety. Grounded in an extensive literature review and underscored by the implementation in two case studies—the Search for Hidden Particles (SHiP) experiment at CERN and the Basilica of Santa Croce’s façade maintenance in Florence—this research demonstrates BIM’s significant impact on reducing accidents, ensuring adherence to safety protocols, and streamlining project execution. Comparative analysis with traditional methods confirms BIM’s superiority in risk mitigation, safety outcomes, and project efficiency. Stakeholder feedback further validates the methodology’s effectiveness, marking a shift towards its broader adoption for safer, more efficient construction practices. Future directions suggest exploring BIM’s scalability, integration with emerging technologies, and long-term impacts on safety and sustainability, aiming for its standardization across the construction industry.
Cover Crops and Tillage: Effects on Soil Chemical Properties and Rice Yield
Authors: Nascimento Vagner do , Arf Orivaldo , Alves Marlene Cristina , de Souza Epitácio José , da Silva Paulo Ricardo Teodoro , Kaneko Flávio Hiroshi , Teixeira Filho Marcelo Carvalho Minhoto , Prado Evandro Pereira , Ferrari Samuel , de Souza Loiane Fernanda Romão , Galindo Fernando Shintate
Published: May 2024

Mechanical soil intervention with a chisel in cover crops (CCs) is a promising strategy for minimizing the superficial compaction of soil in a no-tillage system (NTS). The objective of this study was to evaluate the effect of mechanical chiseling associated with successive crops and preceding cover crops to assess grain yield and changes in soil chemical properties after rice cultivation for two consecutive years. The experimental design comprised randomized blocks in a 5 × 2 factorial scheme with four replications. The treatments consisted of five cover crops (Cajanus cajan, Crotalaria juncea, Urochloa ruziziensis, Pennisetum glaucum, and fallow), with or without soil mechanical chiseling. Soil samples from the 0–5, 5–10, 10–20, and 20–40 cm layers were collected, and the chemical properties were analyzed after rice cultivation. Under U. ruziziensis, the chemical properties were improved by mechanical scarification; however, the initial acidity increased in the 5–40 cm layer. The cultivation of P. glaucum and C. juncea prior to rice, regardless of scarification, improved the soil chemical properties in the 0–40 cm layer. Mechanical soil scarification and the use of C. cajan as a cover crop increased the grain yield of upland rice by approximately 552 and 1454 and 1330 kg ha−1 compared to the P. glaucum and U. ruziziensis, respectively.
Unveiling Microplastic Abundance and Distribution in an Oceanic Island: Offshore Depository or Local Pollution Indicator
Authors: Amorim Luísa Madalena , Costa José Lino , Costa Ana Cristina , Botelho Andrea Zita , Torres Paulo
Published: May 2024

Millions of tons of solid waste, mostly plastics, are annually dumped into the oceans, posing a major 21st-century environmental threat. Commercial shipping and ocean gyres exacerbate pollution on remote islands, resulting in the widespread presence of microplastics throughout the marine environment. Most of this pollution is plastics, and its fragmentation originates from microplastics (particles smaller than 5 mm). These debris are ubiquitous throughout the marine environment, dispersed among beaches, estuaries, on the water surface, and even on the seafloor. This study was carried out on São Miguel Island, Azores, where sediment samples were collected and analysed for microplastic (MP) abundance and dimension across eight areas covering the entire coastline of the island. Each area was divided into four sites along an inland–coastal gradient, from the stream to the ocean (upstream, downstream, coastal, and submerged marine sediments), following a nested design approach. In addition to this first method, 15 beaches, spread along the island’s shore, were also tested and compared. Fibres were the most common type of microplastic, with varying levels of abundance across different locations. Abundance generally increased closer to the coast, but there were occasional instances of high upstream concentrations due to heavy rains, which then accumulated near coastlines and beaches. This study revealed an important local MP source from an apparently pristine touristic region which, aligned with other recent findings, unveils an important and silent pollution issue potentially affecting oceanic islands that should be seriously addressed in future studies and raise concern for litter management and mitigation and environmental awareness actions.
Spatiotemporal Effects and Optimization Strategies of Land-Use Carbon Emissions at the County Scale: A Case Study of Shaanxi Province, China
Authors: Zhang Yahui , Li Jianfeng , Liu Siqi , Zhou Jizhe
Published: May 2024

Land use, as one of the major sources of carbon emissions, has profound implications for global climate change. County-level land-use systems play a critical role in national carbon emission management and control. Consequently, it is essential to explore the spatiotemporal effects and optimization strategies of land-use carbon emissions at the county scale to promote the achievement of regional dual carbon targets. This study, focusing on Shaanxi Province, analyzed the spatiotemporal characteristics of land use from 2000 to 2020. By establishing a carbon emission evaluation model, the spatiotemporal effects of county-level carbon emissions were clarified. Utilizing Geodetector and K-means clustering methods, the driving mechanisms and clustering characteristics of county-level carbon emissions were elucidated, and optimization strategies for land use carbon emission were explored. The results showed that during 2000–2020, land use in Shaanxi Province underwent significant spatiotemporal changes, with constructed land increasing by 97.62%, while cultivated land and grassland were substantially reduced. The overall county-level carbon emissions exhibited a pattern of North > Central > South. The total carbon emissions within the province increased nearly fourfold over 20 years, reaching 1.00 × 108 tons. Constructed land was the primary source of emissions, while forest land contributed significantly to the carbon sink of the study area. Interactions among factors had significant impacts on the spatial differentiation of total county-level carbon emissions. For counties with different types of carbon emissions, differentiated optimization strategies were recommended. Low-carbon emission counties should intensify ecological protection and rational utilization, medium-carbon emission counties need to strike a balance between economic development and environmental protection, while high-carbon emission counties should prioritize profound emission reduction and structural transformation.
Pollution Havens in South-East Asia: Examining Japanese Multinational Enterprises in the Philippines
Authors: Ike Masayoshi , Donovan Jerome Denis , Topple Cheree , Masli Eryadi Kordi
Published: May 2024

Of the significant foreign investment by Japanese multinationals within South-East Asia, the Philippines is a key recipient and location for the establishment of subsidiaries. While foreign investment is thought to bring significant benefits to host nations, the Philippines is considered ecologically vulnerable with extensive pollution and environmental challenges. Within national contexts of this nature, debates ensue about manufacturing multinational enterprises using emerging markets or developing nations as pollution havens when their environmental regulations are less stringent than those of the home nation. This study adopts a case study approach to explore the behaviour of Japanese multinationals operating in the Philippines with respect to environmental regulations. The study’s findings indicate that the firms demonstrated environmental management practices at a level beyond requirements set by local laws and regulations, with supplementary benefits to the surrounding local communities. These results indicate that the Philippines’ environmental regulations could be strengthened or tightened up with little negative impact on the investment of Japanese manufacturing multinational enterprises. With scant research conducted at the organisational level, our research findings contribute to a multinational management perspective on pollution haven/halo research, providing an additional dimension alongside the macroeconomic and large-scale environmental effects.