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The accounting profession plays a crucial role in serving public interest by establishing the foundation for sustainable development and taking on social responsibility. The growing focus on sustainability practices of companies and stakeholders has also had a significant impact on the role of accounting and professional accountants. This has led to increased expectations for greater involvement in integrating sustainability into corporate decision making at every level. We used a bibliometric analysis of academic literature as a research method to identify the relationships between accounting, professional accountants, and sustainability issues (APASI). Bibliometrix R-package and VOSviewer were used to achieve the proposed objectives. This study analyzes the performance of the scientific literature, establishes the conceptual, intellectual, and social structure of research, and identifies new research directions. A period of 37 years (1987–2024) is taken into consideration, with 2556 documents and 859 sources extracted from the Web of Science database analyzed. We offer, in an original manner, descriptive statistics and relevant landmarks of the sources, authors, publications, organizations, and countries that have contributed significantly to the development of research in this field. Interested researchers have the opportunity to identify scholars for potential collaborations and valuable study resources. Full article

This paper proposes an innovative transient stability index (TSI) designed to enhance the real-time assessment of power system stability. The TSI integrates a corrected kinetic energy approach with a modified equal area criterion, offering a novel methodology for evaluating transient stability margins in power systems. Unlike traditional methods, the proposed TSI operates without relying on post-fault data, making it particularly suitable for online applications. A structure-preserving model is utilized to represent the power network, accounting for key factors such as controller behavior during transient events. Additionally, a new statistical classification method is introduced to efficiently determine the individual contribution of generators to the overall system stability. The effectiveness of the proposed approach is validated through comprehensive case studies on IEEE 9-bus and IEEE 39-bus systems. The simulation results confirm that the proposed method provides accurate, real-time insights into the transient stability margins of power systems, demonstrating its practical advantages in both analysis and operation. Full article

Designing maintenance strategies for a vast portfolio of aging infrastructures requires decision-makers to ensure adequate safety levels while addressing the requirements on service interruptions, costs, and workforce availability. This study addresses the problem of scheduling maintenance interventions for a portfolio of bridges, aiming to minimize $C{O}_2$ emissions while meeting minimum reliability requirements and adhering to workforce and budget constraints. To achieve this, we present a Simheuristic algorithm that combines a metaheuristic core based on the Adaptive Large Neighborhood Search metaheuristic with a Monte Carlo simulation module. This integration allows for the evaluation of optimized scheduling solutions, accounting for the inherent randomness in the structural deterioration process. The proposed approach is tested in a comparative analysis against traditional time-based and condition-based scheduling methods. Results from diverse bridge portfolios demonstrate that the proposed algorithm offers improved performance in terms of both total costs and $C{O}_2$ emissions. Full article

Driven by global sustainability trends, Building Information Modelling (BIM) technology is increasingly becoming a key tool in the construction industry to improve efficiency and sustainability. This study aims to identify the key factors affecting BIM implementation in the context of Environmental, Social, and Governance (ESG) and Sustainable Development Goals (SDGs) and to construct a theoretical framework for BIM implementation based on these factors. To achieve this objective, this study used a systematic literature review (SLR) method to systematically review the relevant literature between 2009 and 2024 and identified 16 key factors from the selected 406 studies through keyword co-occurrence analysis (using VOSviewer 1.6.20) and data coding. These key factors include top management support for ESG and SDGs, alignment of SDGs, ESG integration, technical support, BIM software, BIM hardware, structural adjustment and collaboration, capacity building, change management, skill and attitude, educational training and development, incentive mechanism, roles and responsibilities, sustainable construction practices, policies and regulations, and resource efficiency. This study categorises these factors under the Strategy, Technology, Organisation, People, Environment (STOPE) framework and proposes a theoretical implementation framework for BIM accordingly. The findings not only provide a practical guiding framework for the sustainable development of construction companies in the context of ESG and SDG integration but also lay a solid theoretical foundation for future empirical research. Full article

Asthma is a chronic inflammatory process that leads to airway narrowing, causing breath loss followed by spasms, wheezing, and shortness of breath. Within the asthmatic lungs, interaction among various immune cells and structural cells plays a significant role in orchestrating an inflammatory response in which eosinophils hold central importance. In these settings, allergens or other environmental exposures commonly drive the immune response to recruit eosinophils to the airways. The appearance of eosinophils in the airways indicates a dynamic interplay of various cell types within lung tissue and does not represent a passive effect of inflammation. The cellular cross-talk causes the persistence of eosinophilic inflammation, and if left untreated, it results in long-term damage to the airway structure and function. Further exacerbation of the condition occurs because of this. We discuss how this complex interplay of eosinophils, immune, and structural cells within the airway microenvironment leads to the distinct pathophysiological features in asthma, the variability in disease severity, and the response to biological treatments. Full article

The satellite-based estimation of forest variables including forest biomass relies on model-based approaches since forest biomass cannot be directly measured from space. Such models require ground reference data to adapt to the local forest structure and acquired satellite data. For wide-area mapping, such reference data are too sparse to train the biomass retrieval model and approaches for calibrating that are independent from training data are sought. In this study, we compare the performance of one such calibration approach with the traditional regression modelling using reference measurements. The performance was evaluated at four sites representative of the major forest biomes in Europe focusing on growing stock volume (GSV) prediction from time series of C-band Sentinel-1 and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS-2 PALSAR-2) backscatter measurements. The retrieval model was based on a Water Cloud Model (WCM) and integrated two forest structural functions. The WCM trained with plot inventory GSV values or calibrated with the aid of auxiliary data products correctly reproduced the trend between SAR backscatter and GSV measurements across all sites. The WCM-predicted backscatter was within the range of measurements for a given GSV level with average model residuals being smaller than the range of the observations. The accuracy of the GSV estimated with the calibrated WCM was close to the accuracy obtained with the trained WCM. The difference in terms of root mean square error (RMSE) was less than 5% units. This study demonstrates that it is possible to predict biomass without providing reference measurements for model training provided that the modelling scheme is physically based and the calibration is well set and understood. Full article

This study aims to address the need for design guidelines in developing a cultural-heritage-based metaverse educational system. Using the UTAUT, the TTF model, and Flow Theory, a theoretical framework is constructed. Through qualitative research based on the GT, three user perception factors—presence, interactivity, and narrativity—are introduced as external variables to explore the relationship between these factors and users’ willingness to adopt the cultural heritage metaverse system. The study examines this relationship from the dual perspectives of user perception and technology acceptance. A scale was designed to test the theoretical model empirically, and 298 valid responses were collected through a structured process involving GT coding, pre-testing, and formal surveys. The findings indicate that interactivity, narrativity, and presence significantly enhance the flow experience, while factors such as performance expectancy, effort expectancy, social influence, facilitating conditions, technology–task fit, and flow positively influence users’ intention to adopt the system. Among these, technology–task fit emerged as the most influential factor. This integrated approach reduces subjectivity and bias in criteria determination, enhancing the objectivity and precision of cultural heritage metaverse system assessments and making the system more responsive to user needs. Full article

The objective of this paper is to explore the potential of integrating three distinct functionalities into a thin, single-layer metasurface. Specifically, the study introduces a metasurface design that combines absorption, polarization conversion, and transmission capabilities. The proposed structure consists of a double square loop disposed on a dielectric substrate, which is covered by a superstrate. In this study, the traditional ground plane was replaced with a periodic array, selectively reflecting frequencies of interest. Then, the absorption and polarization conversion characteristics were achieved by introducing the resonators in the front layer. By introducing asymmetry to the resonators and integrating PIN diodes for control, we demonstrated that the metasurface could efficiently absorb electromagnetic waves (with PIN diodes in the ON state), convert polarization (with PIN diodes in the OFF state), and enable signal transmission in a different frequency range. The numerical results indicated excellent performance in both absorption and polarization conversion. At a frequency of 3.05 GHz, the absorption rate reached 97%, while a polarization conversion rate of 98% was achieved at the resonance frequency of 4.37 GHz. Moreover, the proposed structure exhibited a thickness of λ/30.7 at the absorption peak. Full article

As of January 2024, Ukraine has suffered the extensive destruction of over 160,000 buildings, structures, and infrastructure objects due to the shelling resulting from the ongoing war. After the conflict, the country will undergo large-scale reconstruction, following European standards. However, Ukraine’s construction industry remains somewhat outdated, particularly in digital technologies like BIM (Building Information Modeling). Despite this, Ukraine has a growing number of young professionals providing BIM services to international clients. A collaborative study between Loughborough University (UK) and the O.M. Beketov National University of Urban Economy (Ukraine) examined the current state of BIM in Ukraine. The research aimed to develop a strategy for integrating BIM into post-war reconstruction, based on a review of the design and construction sectors. The findings showed that BIM use in Ukraine is driven by international market demands, requiring changes in how BIM is adopted locally. A survey of 234 employees from Ukrainian outsourcing companies and interviews with seven large construction firms in Eastern Ukraine revealed barriers to BIM adoption. These included low wages, a lack of incentives for large firms, bureaucratic inefficiencies, corruption, outdated construction management, and weak regulations. This study provides recommendations to accelerate BIM integration in Ukraine’s construction industry during the post-war rebuilding phase. Full article

In order to enhance the sensitivity of elastomers, pores were integrated into their structure. These pores facilitate the adjustment of thickness in response to external pressure variations, thereby improving the sensitivity of pressure sensors. Pores were introduced by emulsifying immiscible polydimethylsiloxane (PDMS) and water with a surfactant. By controlling the water content in the PDMS and water emulsion, we controlled the size, density, uniformity, and spatial distribution (2D or 3D) of the pores within the PDMS matrix. The presence of these pores significantly improved the sensitivity of PDMS under low external pressure conditions compared to high pressures. Specifically, porous PDMS exhibited approximately 10-times greater sensitivity under low-pressure conditions than non-porous PDMS. The effectiveness of porous PDMS was demonstrated through dynamic loading and unloading detection of a small Lego toy and monitoring of human heartbeats. These results highlight the efficacy of our pressure sensor based on porous PDMS, which is fabricated through a simple and cost-effective process using a PDMS and water emulsion. This approach is highly suitable for developing the ability to detect applied pressures or contact forces. Full article

With the rapid progression of urbanization, Chinese cities are encountering an increasingly severe shortage of land resources. To examine the role of digital finance (DF) in promoting economic agglomeration (EA) and subsequently improving urban land use efficiency (ULUE), this paper focuses on 274 prefecture-level cities from 2013 to 2020. By employing an interaction effect model, the study analyzes how DF influences the relationship between EA and the enhancement of ULUE. The findings demonstrate that DF positively moderates the effect of EA on enhancing ULUE. The analysis reveals that DF can accelerate resource flows and more effectively promote the enhancement of ULUE by amplifying the positive influence of EA on regional innovation ability (IA) and the rationalization of industrial structures (RIS). Furthermore, the heterogeneity analysis indicates that this moderating effect is particularly pronounced in China’s central and eastern regions, areas with higher rates of internet penetration, and regions with stronger innovation capacities. Based on these findings, this paper proposes policy recommendations such as promoting regional integration and supporting innovation in DF. These insights contribute to the theoretical discourse on EA in the digital era and provide critical and practical guidance for optimizing the development of agglomeration economies and constructing a high-quality development framework. Full article

Line charts are prevalent in scientific documents and commercial data visualization, serving as essential tools for conveying data trends. Automatic detection and tracing of line paths in these charts is crucial for downstream tasks such as data extraction, chart quality assessment, plagiarism detection, and visual question answering. However, line graphs present unique challenges due to their complex backgrounds and diverse curve styles, including solid, dashed, and dotted lines. Existing curve detection algorithms struggle to address these challenges effectively. In this paper, we propose ChartLine, a novel network designed for detecting and tracing curves in line graphs. Our approach integrates a Spatial-Sequence Attention Feature Pyramid Network (SSA-FPN) in both the encoder and decoder to capture rich hierarchical representations of curve structures and boundary features. The model incorporates a Spatial-Sequence Fusion (SSF) module and a Channel Multi-Head Attention (CMA) module to enhance intra-class consistency and inter-class distinction. We evaluate ChartLine on four line chart datasets and compare its performance against state-of-the-art curve detection, edge detection, and semantic segmentation methods. Extensive experiments demonstrate that our method significantly outperforms existing algorithms, achieving an F-measure of 94% on a synthetic dataset. Full article

In this paper, we extend prominent fixed-point theorems within the framework of symmetry, a structure increasingly relevant in decision-making, optimization, and uncertainty modeling. While previous studies have explored fixed-point theorems in non-Archimedean spaces, the influence of symmetry on the properties of mappings remains underexamined. To address this gap, we introduce and analyze the concepts of $\chi$-contractions and $\chi$-weak contractions, demonstrating how symmetry impacts the conditions for the existence of fixed points. Our methodology integrates these concepts in generalized neutrosophic metric spaces, providing a novel perspective on fixed-point theory. We perform a rigorous analysis, revealing new insights into their practical applications. However, our proposed system may face limitations in complex or dynamic environments, where additional conditions may be necessary to ensure the existence or uniqueness of fixed points. Full article

Change detection (CD) identifies surface changes by analyzing bi-temporal remote sensing (RS) images of the same region and is essential for effective urban planning, ensuring the optimal allocation of resources, and supporting disaster management efforts. However, deep-learning-based CD methods struggle with background noise and pseudo-changes due to local receptive field limitations or computing resource constraints, which limits long-range dependency capture and feature integration, normally resulting in fragmented detections and high false positive rates. To address these challenges, we propose a tree topology Mamba-guided network (TTMGNet) based on Mamba architecture, which combines the Mamba architecture for effectively capturing global features, a unique tree topology structure for retaining fine local details, and a hierarchical feature fusion mechanism that enhances multi-scale feature integration and robustness against noise. Specifically, the a Tree Topology Mamba Feature Extractor (TTMFE) leverages the similarity of pixels to generate minimum spanning tree (MST) topology sequences, guiding information aggregation and transmission. This approach utilizes a Tree Topology State Space Model (TTSSM) to embed spatial and positional information while preserving the global feature extraction capability, thereby retaining local features. Subsequently, the Hierarchical Incremental Aggregation Module is utilized to gradually align and merge features from deep to shallow layers to facilitate hierarchical feature integration. Through residual connections and cross-channel attention (CCA), HIAM enhances the interaction between neighboring feature maps, ensuring that critical features are retained and effectively utilized during the fusion process, thereby enabling more accurate detection results in CD. The proposed TTMGNet achieved F1 scores of 92.31% on LEVIR-CD, 90.94% on WHU-CD, and 77.25% on CL-CD, outperforming current mainstream methods in suppressing the impact of background noise and pseudo-change and more accurately identifying change regions. Full article

Smart technology is essential for integrating circular economy principles. This research investigates how conflict management strategies (collaboration, accommodation, avoidance, compromise, and competition) impact the adoption of smart technology, particularly blockchain, in Jordanian SMEs. Additionally, the study explores the moderating role of customer-centric green supply chain management in the relationship between blockchain adoption and circular economy principles. This research addresses a gap in the literature by focusing on Jordanian SMEs, an under-explored context. Data were collected from 421 senior managers, department heads, and executives of Jordanian SMEs, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), to test the hypotheses and analyze complex relationships. The findings reveal that conflict management strategies are critical in blockchain adoption, with collaboration and compromise emerging as the most influential. Moreover, blockchain adoption positively impacts the implementation of circular economy principles. The moderating effect of customer-centric green supply chain management enhances the sustainability and competitiveness of SMEs through blockchain technology. This research contributes to theory and practice by providing valuable insights into the strategic role of conflict management in driving technological innovation and sustainability within the circular economy framework, particularly in the context of Jordanian SMEs. Full article