Search Results (411)

Sensors are a key component of virtual reality (VR) technology, as they enable motion tracking, interaction with the environment, and realistic representation of user behaviour in virtual space. VR technology is gaining increasing importance in engineering, offering new ways to support research, analysis, and training. This article examines its applications in four key areas: surveying and geomatics, mining, environmental protection, and occupational safety. The study is based on a review of the scientific literature indexed in the Scopus database, with the aim of highlighting both the potential of VR and directions for its future development. The findings indicate that VR provides effective tools for analyzing, interpreting, and visualizing complex geospatial data. It enables realistic simulations of mining processes, supports the monitoring of environmental impacts, and facilitates environmental education by creating engaging, immersive experiences. In occupational safety, VR allows hazard scenarios and accident events to be reproduced in a safe yet highly realistic environment, significantly enhancing the effectiveness of training. This is made possible through the integration of sensors with virtual reality, further enhancing immersion in the environment. Despite these advantages, several barriers have been identified. They include technological challenges, insufficient numbers of trained specialists, health and ergonomics concerns, resistance to organizational change, ethical considerations, and limited funding. It is clear that the future of VR in engineering will be shaped by continuous technological progress combined with growing attention to behavioural aspects of training and user interaction. These trends are expected to drive the creation of increasingly advanced and effective tools. The article thus provides a foundation for further exploration of VR as an integral part of engineering practice. Full article

Variable renewable energy sources and cross-zonal trades stress transmission grids, pushing them toward thermal limits. This systematic review, reported in accordance with PRISMA 2020, examines how demand-side response (DSR) can provide relief at the transmission scale. We screened peer-reviewed literature and operator documentation, from 2010 to 2025, indexed in Web of Science, Scopus, and IEEE Xplore; organized remedial actions across supply, network, and demand/storage levers; and categorized operational attributes (time to effect, spatial targeting, activation lead times, telemetry, and measurement and verification). Few reviewed sources explicitly link DSR to transmission congestion relief, highlighting the gap between its mature use in frequency and adequacy services and its still-limited, location-specific application on the grid. We identify feasibility conditions, including assets downstream of the binding interface, minute-scale activation, and feeder-grade baselines with rebound accounting. This implies the following design requirements: TSO–DSO eligibility registries and conflict resolution, portfolio mapping to power-flow sensitivities, and co-optimization with redispatch, HVDC, topology control, and storage within a security-constrained optimal-power-flow framework. No full-text risk-of-bias assessment or meta-analysis was undertaken; the review used English-only title/abstract screening. Registration: none. Funding: none. Full article

This study investigates the dynamic relationship between key macroeconomic indicators, specifically inflation (CPI), the Federal Funds Rate, GDP growth, unemployment, and money supply, and U.S. stock market returns, represented by the S&P 500 index, over the period January 2015 to June 2025. The objective is to understand how inflation and monetary policy affect market performance in both the short and long run. Using an Autoregressive Distributed Lag (ARDL) modeling framework and Error Correction Model (ECM), the study examines monthly S&P 500 returns alongside macroeconomic variables, accounting for lagged effects and potential cointegration. The model captures both immediate and delayed impacts, employing the Bounds Testing approach to confirm long-run equilibrium relationships. Results show significant mean-reversion in stock returns, a delayed negative impact of inflation and interest rate increases, and a positive contemporaneous response to GDP growth. Unemployment exhibits a counterintuitive positive effect on returns, suggesting forward-looking investor expectations. The money supply also positively influences equity prices, supporting liquidity-based asset pricing theories. This paper provides updated empirical evidence on macro-finance linkages and highlights the complex interplay of monetary policy, inflation, and market expectations in shaping U.S. equity returns. Full article

Venture capital investment and hedge fund investment are two asset classes of alternative investment fund portfolios. The purpose of this study was to determine whether the digital currency named bitcoin truly adds to diversification in an alternative investment fund portfolio. Vector auto regression was used to determine any unidirectional or bidirectional relationship between variables. The DCC-GARCH test was conducted to determine any conditional correlations that impact volatility transmission over a shorter and longer duration of time between variables. The results showed that there was no unidirectional or bidirectional relationship between bitcoin and FTSE venture capital index, as well as between bitcoin and the Barclays Hedge Fund Index. The DCC model showed no volatility transmission between bitcoin and the Barclays Hedge Fund Index, whereas volatility persists between bitcoin and the FTSE Venture Capital Index, connecting risk between the financial time series with only low correlations. These findings suggest that bitcoin could be used by investors, policy makers, and hedgers for diversification in alternative investment fund portfolios. Full article

The contribution of Higher Education Institutions (HEIs) in achieving UN-Sustainable Development Goals (SDGs) is critical. HEIs’ contribution to the SDGs is not only confined to education and research but also to their engagement with society, policy-ma-king, infrastructure establishment, and sustainability practice in the institution. By aligning their programs and projects to the SDGs, HEIs can share significantly, producing a more sustainable development for all. One of the notable investments of Davao Oriental State University (DOrSU) is the construction of the University Research Complex (UResCom). The structure contains the university’s research laboratories and working spaces for academic scholars to conduct cutting-edge research and scientific breakthroughs. The seed fund for the laboratory equipment and initial research participation was sponsored by project grants from the Department of Science and Technology—Philippine Council for Industry, Energy, and Emerging Technology Research and Development (DOST-PCIEERD). Partnering with established laboratories and institutions is also an effective tool to guide developing universities. This approach will strengthen more productive research engagements as one of the prime movers of the university’s development. It will enhance scientific research outputs and coverage, improve the faculty’s technological competence, enable partnerships with the industrial sector, and is a leverage for the submission of project proposals. This approach will significantly contribute to improving the country’s Global Innovation Index (GII) ranking and to the achievement of these goals. Full article

The purpose of this research is to systematically map and analyze the use of AI technologies in project management, identifying themes, research gaps, and practical implications. This study conducts a systematic literature review (SLR) that combines bibliometric analysis with qualitative content evaluation to explore the present landscape of AI in project management. The search covered literature published until November 2024, ensuring inclusion of the most recent developments. Studies were included if they examined AI methods applied to project management contexts and were published in peer-reviewed English journals as articles, review articles, or early access publications; studies unrelated to project management or lacking methodological clarity were excluded. It follows a structured coding protocol informed by inductive and deductive reasoning, using NVivo (version 12) and Biblioshiny (version 4.3.0) software. From the entire set of 1064 records retrieved from Scopus and Web of Science, 27 publications met the final inclusion criteria for qualitative synthesis. Bibliometric clusters were derived from the entire set of 885 screened records, while thematic coding was applied to the 27 included studies. This review highlights the use of Artificial Neural Networks (ANN), Case-Based Reasoning (CBR), Digital Twins (DTs), and Large Language Models (LLMs) as central to recent progress. Bibliometric mapping identified several major thematic clusters. For this study, we chose those that show a clear link between artificial intelligence (AI) and project management (PM), such as expert systems, intelligent systems, and optimization algorithms. These clusters highlight the increasing influence of AI in improving project planning, decision-making, and resource management. Further studies investigate generative AI and the convergence of AI with blockchain and Internet of Things (IoT) systems, suggesting changes in project delivery approaches. Although adoption is increasing, key implementation issues persist. These include limited empirical evidence, inadequate attention to later project stages, and concerns about data quality, transparency, and workforce adaptation. This review improves understanding of AI’s role in project contexts and outlines areas for further research. For practitioners, the findings emphasize AI’s ability in cost prediction, scheduling, and risk assessment, while also emphasizing the importance of strong data governance and workforce training. This review is limited to English-language, peer-reviewed research indexed in Scopus and Web of Science, potentially excluding relevant grey literature or non-English contributions. This review was not registered and received no external funding. Full article

Bridges are critical nodes in freight networks, yet limited funding prevents agencies from maintaining all structures in good condition. This creates the need for a transparent and scalable method to identify which bridges pose the greatest risk to supply chain continuity. This study develops a bridge risk index using the threat–vulnerability–consequence (TVC) framework and validates its components with machine learning. Threat is defined as per-lane average daily traffic, vulnerability as effective bridge age (epoch), and consequence as detour distance, with traffic also contributing to disruption magnitude. The methodology applies log transformation and normalization to construct an interpretable multiplicative index, then classifies risk using Jenks natural breaks. The results show that epoch dominates vulnerability, detour distance amplifies consequence, and their interaction explains most of the risk variation. Specifically, effective age explains over three times more variation in bridge condition than any other attribute. The vulnerability–consequence interaction dominates with an R² = 0.98. The highest-risk bridges are concentrated in rural areas and near major freight gateways where detour options are limited. The proposed TVC index provides a transparent, data-driven decision-support tool that agencies can apply nationwide to prioritize investments, safeguard freight corridors, and strengthen supply chain resilience. Full article

Worldwide educators have been devoting resources to quality education and achieving Sustainable Development Goals. Taiwan strategically implemented the Higher Education Sustained Progress and Rise of Universities in Taiwan (SPROUT) Project with an equity-oriented resource allocation. This study aims to investigate the effectiveness of SPROUT’s implementation by analyzing 2018 to 2023 data. In this study, we construct a Fiscal Sustainability Index and other Institutional Performance Index to assess institutions. The two-way fixed effects regression model is applied to investigate the causal relationship among FSI, institutional performance, and the implemented effect of the SPROUT Project. The results of this study showed that the SPROUT Project has not fully achieved all four core objectives, and regional disparities still persisted. In other words, the elite universities in northern Taiwan still receive the most SPROUT Project funding and outperform other universities in other regions. FSI is positively associated with publicness, social responsibility, and overall institutional performance. The results of this study show how higher education institutions can achieve partial sustainable development goals of Goal 2030 via fiscal sustainability and equitable resource allocation. Taiwan’s pivot toward an equity-funding paradigm and supplement with performance-based grants has attenuated the historical concentration of resources among elite universities. Quality education should be inclusive, equitable, and accessible in education and sustainable resources. Full article

This benchmarking study situates Jordan’s trade indicators relative to comparators (Egypt, Lebanon, Saudi Arabia, and the United Arab Emirates) with descriptive analysis. Using indicators for port competitiveness, geopolitical stability, logistics infrastructure, and trade facilitation within a Modified Input–Process–Output framework, based on secondary data from conventional international indicators (“Fund for Peace Fragile States Index,” “Institute for Economics & Peace Global Peace Index,” “OECD Trade Facilitation Indicators,” “UN Comtrade Trade Volume Records, 2022–2023,” “UN Conference on Trade and Development Port Performance Scorecard,” and “World Bank Logistics Performance Index”). The outcomes of this analysis demonstrate that Jordan’s strengths in terms of institutional quality and geopolitical stability are countermanded by relatively poor digital technology adoption and governance of ports, and homogeneity in exports. Using M-IPO model and SWOT analysis, it was identified that specific actions are needed to improve Jordan’s trade performance, especially as a hub for regional logistics, including investment and facilitation of digital system adoption, commensurate infrastructure, and flexibility in governance. Full article

In recent years, the field of European funds for business development has generated significant interest in the academic literature, stimulated by European Union (EU) regulations and the implementation of business financing programs. This context has led to an increase in research on the impact and use of European funds, particularly in terms of support for economic development and infrastructure. This paper presents a bibliometric analysis, using topic modeling, to examine academic publications on the use and absorption of European funds and how they influence the business environment. Using a dataset of 74 publications indexed in the Clarivate Analytics Web of Science Core Collection, covering the period 2005–2024, the present study aims to identify the main authors, institutions, journals, and collaboration networks involved. It also analyzes research trends, dominant themes, and the countries with the largest contributions in this field, using Latent Dirichlet Allocation (LDA) and BERTopic analysis as a complement to the classical bibliometric approach. The thematic analysis reveals a thematic cohesion around entrepreneurship, EU structural funds, regional development, and innovation. In addition, there has been a significant annual increase in publications in this field, and through the use of thematic maps, word clouds, and collaboration networks, this study provides an overview of the evolution of research on the absorption of European funds and its impact on the business environment. These findings contribute both to deepening academic knowledge and to formulating more effective European policies for optimizing fund absorption and supporting the sustainable development of the business environment. Full article

Sustainable investing has grown rapidly, but it remains unclear whether actively managed sustainable funds outperform passive ones. This study compares the performance of high-sustainable active U.S. equity mutual funds and their index peers from September 2018 to April 2022, dividing the period into pre-crash, crash, and post-crash phases around the COVID-19 market downturn. On average, both active and index funds underperform, with the sharpest losses occurring during the crash. High-sustainable funds outperform low-sustainable ones, particularly during the crash. However, high-sustainable active funds do not outperform their passive counterparts in any period. These results suggest that active management does not offer greater downside protection and raise questions about the higher fees typically charged by actively managed sustainable funds. Full article

Background: Although evidence-based practice is widely promoted in nursing, direct care nurses remain underrepresented in research activities. This study aimed to assess nurses’ attitudes toward research, their perceptions of the organizational research environment, and their levels of involvement, as well as identify key barriers and facilitators to engagement within a comprehensive healthcare system. This study also explored how racial and ethnic diversity within the nursing workforce may shape research engagement and contribute new perspectives to the field. Methods: A cross-sectional electronic survey was administered to registered nurses across 10 hospitals in a Northeast U.S. health system. The survey instrument assessed research attitudes, environment, involvement (past, present, future), and demographics. Descriptive and inferential statistics, including matched-pairs t-tests, were used to analyze responses. Results: Of 7655 invited nurses, 1094 responses were analyzed. Respondents were predominantly female (88.5%), White (56.8%), and employed full-time (87.1%) as clinical staff nurses (77.3%). While 54.8% had completed a formal research course (mainly within the past 1–3 years), informal research and statistics training were uncommon (17.4% and 5.4%, respectively). Nurses reported highly positive attitudes toward research (composite M = 2.15, SD = 0.51), especially its role in guiding practice, professional growth, and education. However, actual involvement was low. The most common current activities included practice change based on research (20.7%) and participation in committees (18.8%). Anticipated future engagement increased substantially, particularly in collaboration (+21.3%), committee participation (+20.6%), and IRB submission (+18.2%). The research environment was perceived as under-resourced, particularly in terms of protected time, funding, and mentorship. Statistically significant gaps were observed between perceived present and desired future supports (p < 0.01 for all 15 items). The Research Awareness Index revealed high rates of uncertainty about available resources (e.g., 66.1% did not know if internal funding existed). Conclusions: Nurses demonstrate strong positive attitudes and a desire to engage in research, including more advanced roles. Yet structural and informational barriers, particularly a lack of protected time, mentorship, and awareness of existing supports, limit participation. Investments in infrastructure, communication, and accessible development pathways are needed to translate nurses’ readiness into active research engagement. Implications: Institutions should prioritize making research support more visible and navigable while investing in mentorship, protected time, and user-friendly infrastructure. Addressing both facets will empower a highly motivated nursing workforce to engage in and lead practice-relevant research. Full article

Bridges play an increasingly indispensable role in endorsing the economic and social development of societies by linking highways and facilitating the mobility of people and goods. Concurrently, they are susceptible to high traffic volumes and an intricate service environment over their lifespans, resulting in undergoing a progressive deterioration process. Hence, efficient measures of maintenance, repair, and rehabilitation planning are critical to boost the performance condition, safety, and structural integrity of bridges while evading less costly interventions. To this end, this research paper furnishes a mixed review method, comprising systematic literature and scientometric reviews, for the meticulous examination and analysis of the existing research work in relation with maintenance fund allocation models of bridges (BriMai_all). With that in mind, Scopus and Web of Science databases are harnessed collectively to retrieve peer-reviewed journal articles on the subject, culminating in 380 indexed journal articles over the study period (1990–2025). In this respect, VOSviewer and Bibliometrix R package are utilized to create a visualization network of the literature database, covering keyword co-occurrence analysis, country co-authorship analysis, institution co-authorship analysis, journal co-citation analysis, journal co-citation, core journal analysis, and temporal trends. Subsequently, a rigorous systematic literature review is rendered to synthesize the adopted tools and prominent trends of the relevant state of the art. Particularly, the conducted multi-dimensional review examines the six dominant methodical paradigms of bridge maintenance management: (1) multi-criteria decision making, (2) life cycle assessment, (3) digital twins, (4) inspection planning, (5) artificial intelligence, and (6) optimization. It can be argued that this research paper could assist asset managers with a practical guide and a protocol to plan maintenance expenditures and implement sustainable practices for bridges under deterioration. Full article

The marginalisation of the inner areas due to increased social, material, economic and infrastructural vulnerability is a growing phenomenon affecting many countries today. Although, specific policies, measures, and funding have recently been proposed to address this issue, they have been slow to produce the expected results. Those responsible for decision-makers regarding the prospect of territorial rebalancing need support in identifying the residual value of these marginal areas. This will help them recognise where and how this value can be emphasised in an integrated, long-term redevelopment process. Based on an axiological perspective of territorial capital forms, the research project has developed a “Geo-referenced Value-based Knowledge Model” using Multi-attribute Value Theory (MAVT). It plays a key role in estimating the Reaction Capability Index (I_RCI) of Sicily’s “inner areas”. The results demonstrate the reaction capability of the municipalities in these areas. As a measure of the overall endowment of territorial capital, the I_RCI index can help decision-makers National Strategy Inner Areas (NSIA), promote the efficient use of resources, and encourage the effective implementation of policies aimed at rebalancing the territory. Full article

This study examines regional disparities and convergence dynamics in paediatric healthcare accessibility across Poland’s 16 provinces between 2010 and 2023. A synthetic Paediatric Service Accessibility Index (PSA Index), constructed with Hellwig’s method, is combined with socio-economic indicators such as employment, urbanisation, and disposable income to evaluate the alignment between healthcare provision and regional development. The analysis employs non-parametric regional tests (Spearman’s rank correlation, Wilcoxon signed-rank test) and national panel regression models (Fixed and Random Effects). Results demonstrate significant spatial heterogeneity: economically advanced regions, including Mazowieckie and Małopolskie, show moderate to strong convergence between socio-economic progress and healthcare access, whereas structurally weaker regions such as Lubuskie and Podkarpackie reveal persistent divergence. Disposable income and urbanisation emerge as significant predictors of healthcare availability (p < 0.01), while employment is not statistically significant. The findings highlight enduring inequalities that are relevant in the context of the European Union’s (EU) cohesion policy and indicate that economic growth alone is insufficient to ensure equitable access to paediatric care. Comparative evidence from Romania, Bulgaria, and Spain points to similar patterns and emphasises the importance of EU Structural and Investment Funds in promoting healthcare equity. The study concludes that territorially sensitive, multidimensional interventions are necessary to advance social sustainability and to align healthcare infrastructure with the Sustainable Development Goals, particularly SDG 3 (Good Health and Well-Being) and SDG 10 (Reduced Inequalities). Full article