Search Results (2,381)

Earthwork operations constitute a substantial share of infrastructure project costs and are critical to overall project efficiency. However, the construction industry still relies on conventional approaches and there is a lack of integrated fleet management systems for collaboratively working equipment. While telematics is widely used in other industries, its applications to monitor the complex interactions between excavators, dump trucks, and dozers in real time remain limited. This study proposes an intelligent fleet monitoring system that utilizes only satellite navigation data (GNSS) to analyze the real-time productivity of multiple earthwork machines without relying on additional sensors, such as IMU or accelerometers, thereby eliminating the need for separate measurement procedures. A lightweight site configuration step is required to define the work area/loading/dumping geofences on an existing site map. This research provides novel developed algorithms that facilitate a real-time productivity assessment for several earthwork equipment and provide planning-level recommendations for equipment deployment combinations. Dedicated motion classification algorithms were developed for excavators, dump trucks, and dozers to distinguish activity states, to compute working and idle times, and to quantify operational efficiency. The system integrates a web-based e-Fleet Management platform and a mobile e-Map application for visualization and equipment optimization. Field validation was conducted on two active earthwork projects to evaluate accuracy and feasibility. The results demonstrate that the developed algorithms achieved classification and productivity estimation errors within 2.5%, while enabling optimized equipment combinations and improved cycle time efficiency. The proposed system offers a practical, sensor-independent approach for enhancing productivity monitoring, real-time decision-making, and cost efficiency in large-scale earthwork operations. Full article

Under the background of accelerating global transitions towards low-carbon development, digital intelligence transformation (DIT) has become a critical force that helps companies overcome green technological constraints and translate external green pressures into substantive green innovation. Taking the establishment of China’s NAIIDTZs as a quasi-natural experiment, this study investigates the impact of DIT on corporate green innovation (CGI) from an internal decision-making perspective. Based on a panel dataset of 19,440 samples from Chinese A-share listed companies during 2012–2023, our findings show that DIT significantly enhances both the quantity and quality of CGI. Mechanism analyses indicate that DIT promotes CGI’s quantity through increased R&D human capital input, while improving CGI’s quality through managerial myopia reduction. Heterogeneity analyses further reveal that the positive effects of DIT on CGI are particularly pronounced in firms operating under fierce market competition, in high industrial technological intensity, and in eastern regions. Furthermore, we find that CGI exerts a lagged effect on carbon emission reduction performance, while the effect of CGI’s quality is stronger than that of CGI’s quantity. These findings extend the dynamic capacity theory to digitalization and provide practical and policy implications for promoting CGI through digital intelligence development. Full article

A group of experts of different specialties involved in the care of prostate cancer (PCa) patients participated in the ENFOCA2 project, promoted by the Spanish Oncology Genitourinary Group (SOGUG), with the aim to review, discuss, and summarize current relevant aspects related to screening, diagnosis, imaging, risk-based approach, and molecular characterization of PCa. A multidisciplinary team (MDT) approach is essential to ensure that patients receive evidence-based care, promoting shared decision-making, and tailoring treatment to the patient’s unique values and preferences. Population-based screening based on risk-stratified algorithms is needed to overcome the limitations of opportunistic screening for detecting clinically significant PCa. Next-generation imaging (NGI) methods, such as prostate-specific membrane antigen (PSMA) PET/CT alone or combined with multiparametric MRI (mpMRI), have a promising role in different scenarios of the diagnostic process due to their high sensitivity. The diagnostic yield of mpMRI should be improved, especially for assessing extraprostatic extension. The use of specific molecular probes as imaging markers for MRI could improve the staging of metastatic disease. Protocols for germline testing developed by international societies, such as the European Association of Urology (EAU) and the National Comprehensive Cancer Network (NCCN), should be adapted at local levels, with BRCA1/2, ATM, PALB2, CHEK2, MLH1, MSH2, MSH6, PMS2, EPCAM, and HOXB13 as the genes to be investigated. Genomic classifier tools help identifying aggressiveness of cancers and aid in personalized treatment decision-making. Joint efforts of multidisciplinary physicians are crucial to improve health outcomes for patients with PCa across the spectrum of this disease. Full article

This study examines consumer attitudes and experiences related to ride-sharing services in the Western Transdanubia region of Hungary. Despite the growing global popularity of shared mobility solutions, there is little empirical evidence on regional consumer acceptance patterns in the Hungarian context. Based on a structured questionnaire survey involving 500 respondents, this research explores the relationship between satisfaction with past ride-sharing experiences and the intention to reuse such services in the future. The results reveal a high willingness to reuse among those who have already tried ridesharing, yet the correlation analysis shows that satisfaction dimensions alone are not significant predictors of reuse intention. In contrast, attitudinal factors, such as preference over other transport modes, willingness to make recommendations, and perceived accessibility, exhibit strong correlations with acceptance of ride-sharing. The findings emphasise the key role of attitudes and trust in shaping consumer decisions. The paper contributes to the literature by providing regionally grounded empirical insights and offers practical and policy-level recommendations to support the diffusion of sustainable shared mobility services. Full article

Background: Locally advanced rectal cancer is traditionally managed with neoadjuvant chemoradiotherapy followed by total mesorectal excision, but radical surgery entails substantial morbidity, including bowel, urinary, and sexual dysfunction as well as permanent stomas. Organ-preserving strategies such as total neoadjuvant therapy (TNT) followed by a watch-and-wait (WW) approach aim to reduce morbidity while maintaining oncologic safety. A recent study from the FOREST cohort confirmed favorable survival outcomes with WW but did not assess the patient-centered impact. Methods: This retrospective observational study included locally advanced rectal cancer patients treated at a tertiary hospital. Following TNT, patients who achieved a complete clinical response entered WW, while others underwent radical surgery (RS). Patient-reported outcomes were assessed using an 18-item questionnaire grouped into domains and transformed to a 0–100 scale according to EORTC scoring methodology. All patients underwent a shared decision-making process. Comparisons between groups used Pearson chi-square tests for clinical and demographics associations and Mann–Whitney U tests for ordinal outcomes. The protocol was integrated into Quirónsalud’s value-based healthcare framework. Results: Clinical and demographics characteristics did not differ between WW and RS groups. PROMs favored WW in multiple domains: Symptoms/Complications (87 vs. 66; p < 0.001), Psychosocial adaptation (90 vs. 66; p < 0.001), Mental health (90 vs. 78; p = 0.006), and Global quality of life (80 vs. 67; p = 0.011). Bowel and sexual functions were similar between groups, and Care satisfaction was very high for both. Conclusions: TNT plus WW appears to be oncologically safe and confers significant quality-of-life benefits across several domains. These findings support the theory that WW is a value-based, patient-centered strategy for rectal cancer, and this warrants validation in larger, randomized cohorts. Full article

In knowledge-intensive professions such as auditing, positive workplace relationships are essential to effective performance. Yet, the specific mechanisms through which ethical leadership encourages critical, collaborative behaviours, such as knowledge sharing, remain underexplored. This study addresses this gap by examining how organisational justice and interpersonal trust serve as dual pathways that translate ethical leadership into the sharing of knowledge within audit teams. Using a cross-sectional survey design, data were collected from 232 auditing professionals in Iran and analysed via Structural Equation Modelling (SEM). The results confirm that ethical leadership is significantly associated with promoting knowledge sharing. More importantly, this relationship is robustly mediated by both organisational justice and trust, revealing a dual-channel mechanism through which leadership exerts its influence. The primary contribution of this research lies in empirically demonstrating this integrated model, illustrating that ethical leaders foster collaboration not only through direct influence but by systematically cultivating a fair and trustworthy work environment. For audit firms and similar professional service organisations, these findings highlight the practical importance of developing leaders and HR policies that explicitly and consistently prioritise fairness and trust-building to strengthen team dynamics and enhance the flow of knowledge. Full article

In today’s volatile digital environments, conventional data governance practices fail to adequately address the dynamic, context-sensitive, and risk-hazardous nature of data use. This paper introduces DRADG (Dynamic Risk-Adaptive Data Governance), a new paradigm that unites risk-aware decision-making with adaptive data governance mechanisms to enhance resilience, compliance, and trust in complex data environments. Drawing on the convergence of existing data governance models, best practice risk management (DAMA-DMBOK, NIST, and ISO 31000), and real-world enterprise experience, this framework provides a modular, expandable approach to dynamically aligning governance strategy with evolving contextual factors and threats in data management. The contribution is in the form of a multi-layered paradigm combining static policy with dynamic risk indicator through application of data sensitivity categorization, contextual risk scoring, and use of feedback loops to continuously adapt. The technical contribution is in the governance-risk matrix formulated, mapping data lifecycle stages (acquisition, storage, use, sharing, and archival) to corresponding risk mitigation mechanisms. This is embedded through a semi-automated rules-based engine capable of modifying governance controls based on predetermined thresholds and evolving data contexts. Validation was obtained through simulation-based training in cross-border data sharing, regulatory adherence, and cloud-based data management. Findings indicate that DRADG enhances governance responsiveness, reduces exposure to compliance risks, and provides a basis for sustainable data accountability. The research concludes by providing guidelines for implementation and avenues for future research in AI-driven governance automation and policy learning. DRADG sets a precedent for imbuing intelligence and responsiveness at the heart of data governance operations of modern-day digital enterprises. Full article

Objectives: This study explores the feasibility and value of integrating structured patient input into the PICOS (Population, Intervention, Comparator, Outcome, Study design) scoping process for Joint Clinical Assessments under the EU Health Technology Assessment Regulation. Methods: A modified Delphi panel, led by a steering committee composed of two clinicians, one patient expert, and one policy expert, engaged 12 individuals representing patient organizations across 12 European Member States to reach consensus on PICOS elements for CAR-T therapy in pediatric spinal muscular atrophy. Results: The Delphi process effectively facilitated PICOS consolidation and consensus among the 12 patient experts representing diverse EU contexts. Through 3 iterative rounds integrating quantitative rankings and qualitative feedback, the panel achieved strong agreement on key outcomes, intervention delivery, and study design elements, with population eligibility and comparator selection showing heterogeneity. Patient engagement was central: participants emphasized inclusive eligibility criteria, shared decision-making, and the inclusion of caregiver perspectives. The integration of qualitative insights allowed nuanced interpretation of dissent, distinguishing between genuine disagreement and framing effects, thereby enhancing transparency and scientific validity. Importantly, the process revealed patient priorities for outcomes, treatment burden, and evidence trade-offs, informing both PICOS refinement and future health technology assessment (HTA) strategies. This structured, participatory approach demonstrates the feasibility and value of incorporating patient voices systematically into early-stage EU HTA, fostering robust, credible, and context-sensitive consensus on complex rare-disease interventions. Conclusions: The study demonstrates the potential of consensus-building methodologies to enhance transparency, reduce heterogeneity, and support patient-centered evidence generation and decision-making in HTA. Full article

Walkability for non-motorized users is crucial for fostering inclusive, healthy, and sustainable communities. By prioritizing modern human-centered design principles, social equality is promoted for all categories of users, regardless of physical abilities or socio-economic status. Despite the importance of this indicator, a series of inconsistencies that produce inadequate and inaccessible urban space can still be observed in cities. The aim of this paper is to present the methodology for the calculation of the walkability index at the local level. This new methodological procedure considers walkability for pedestrians, with a special focus on people with reduced mobility. Based on specifically defined criteria, initial calculations were performed and integrated into the dynamic walkability index (DWI). One of the main advantages of this index is that it includes the dynamic component of the share of different categories of users in the total sample, which enables simple time modification without repeating the entire procedure. The developed methodology can be used as a tool for ranking existing street segments according to the urgency of reconstruction, while on the other hand promoting equality and inclusion of all categories of users in decision-making processes, thus creating more comfortable and safer environments. Full article

AI technologies are increasingly applied to optimize operations in both port and urban logistics systems, yet integration across the full maritime city chain remains limited. The objective of this study is to assess, using a simulation-based experiment, the impact of an AI-orchestrated control policy on the performance of port–city logistics relative to a baseline scheduler. The study proposes an AI-orchestrated approach that connects autonomous ships, smart ports, central warehouses, and multimodal urban networks via a shared cloud control layer. This approach is designed to enable real-time, cross-domain coordination using federated sensing and adaptive control policies. To evaluate its impact, a simulation-based experiment was conducted comparing a traditional scheduler with an AI-orchestrated policy across 20 paired runs under identical conditions. The orchestrator dynamically coordinated container dispatching, vehicle assignment, and gate operations based on capacity-aware logic. Results show that the AI policy substantially reduced the total completion time, lowered truck idle time and estimated emissions, and improved system throughput and predictability without modifying physical resources. These findings support the expectation that integrated, data-driven decision-making can significantly enhance logistics performance and sustainability in port–city contexts. The study provides a replicable pathway from conceptual architecture to quantifiable evidence and lays the groundwork for future extensions involving learning controllers, richer environmental modeling, and real-world deployment in digitally connected logistics corridors. Full article

In the last year, great advances in the treatment outcomes of advanced EGFR-mutant NSCLC have been achieved. Two combination regimens, amivantamab plus lazertinib and platin-based chemotherapy plus osimertinib, have yielded, in the phase III randomized trials named MARIPOSA and FLAURA 2, statistically and clinically significant improvements in overall survival compared with monotherapy with osimertinib. However, translation to clinical practice of these relevant results is challenging for two main reasons. The first is that we have no evidence-based tools to choose among the two combinations, except their different safety profiles. The second is that combinations are significantly more toxic than osimertinib alone. Thus, osimertinib remains an effective treatment with an excellent safety profile, perhaps to be considered as still the best option in the majority of elderly patients and in all patients that do not intend to trade-off an excess of toxicity with survival prolongment. The safety and efficacy characteristics of the three treatment options are the basis for a patient-tailored treatment choice, but in a significant proportion of patients, a personal and intimate approach to quality of life and survival prolongment is to be considered the main driver within a well-structured shared decision-making process. Full article

Background: The rapid ageing of the cardiovascular population has profoundly transformed clinical practice, with an increasing proportion of patients presenting advanced age, frailty, multimorbidity, and functional vulnerability. Conventional cardiology models, largely derived from younger and selected populations, often fail to adequately address the complexity of cardiovascular care in older adults. Despite the growing development of cardiogeriatrics, the core competencies required for contemporary geriatric cardiology practice remain insufficiently defined. Methods: This narrative review synthesises evidence from cardiology, geriatrics, heart failure, and the palliative care literature, complemented by clinical expertise in integrated cardiogeriatric care pathways, to identify key competencies relevant to the care of older adults with cardiovascular disease. Results: Four major domains of geriatric cardiology competencies were identified: (1) advanced cardiovascular expertise adapted to ageing physiology, frailty, and multimorbidity; (2) integration of comprehensive geriatric assessment into cardiovascular decision-making; (3) a dedicated cardiogeriatric communication mindset supporting shared decision-making under prognostic uncertainty; and (4) system-based competencies focused on multidisciplinary coordination, care transitions, and therapeutic proportionality. Conclusions: Defining the core competencies of the geriatric cardiologist is essential to addressing the clinical and organisational challenges of an ageing cardiovascular population. This framework provides a pragmatic foundation for clinical practice, education, and future research, supporting integrated cardiogeriatric care models aligned with patient-centred outcomes. Full article

Organizational learning refers to the systematic development, exchange and dissemination of knowledge throughout the organization. Organizational learning processes in construction are disrupted by the decentralized flow of information and the temporary, short-term nature of project teams. The emergence of Building Information Modelling (BIM) has significantly enhanced the ability to capture and disseminate construction project knowledge within the architecture, engineering, construction, and facilities management (AEC-FM) sector. Despite this progress, existing research has predominantly focused on the technical aspects of BIM, with limited evidence on its effects on organizational learning capabilities. This study addresses this gap by examining how BIM shapes organizational learning mechanisms within AEC-FM contexts. Employing a systematic literature review (SLR) approach, 104 articles from the Scopus database were analyzed using scientometric and thematic analyses. The systematic review of the literature was carried out following the PRISMA guidelines. The SLR provided a comprehensive examination of BIM’s contribution to strengthening the three core organizational learning mechanisms: experience accumulation, knowledge articulation, and knowledge codification. The thematic analysis revealed seven BIM-enabled organizational learning factors that are expected to strengthen learning mechanisms in AEC-FM organizations: agility of thinking and reasoning skills; enhanced decision-making; interconnected stakeholders’ relationships; integrated business processes; BIM-facilitated project knowledge sharing; BIM-supported project knowledge retention; and BIM-supported project knowledge extraction. Findings suggest that BIM significantly facilitates learning mechanisms within AEC-FM firms. A conceptual model of BIM-supported learning mechanisms was developed to highlight opportunities for enhancing organizational learning capabilities in the BIM environment. Full article

The mobility of data factors and the adoption of a collaborative innovation framework are key drivers influencing the gaps in total factor productivity (TFP) among enterprises in the digital economy. Using panel data from Chinese A-share listed companies between 2006 and 2022, this study empirically demonstrates how data factor flow reduces TFP gaps. The findings reveal that data factor flow enhances TFP convergence by facilitating knowledge diffusion, improving information transmission, and boosting innovation efficiency. However, the heterogeneity in enterprise RD efforts limits this convergence effect, highlighting the importance of collaborative innovation. The study further shows that the impact of data factor flow is more significant in smaller, privately owned enterprises in the eastern regions and in industries with low to high technology intensity and high market concentration. Key insights include (1) a positive synergy between government data openness policies and enterprise data flow, which reinforces the narrowing of TFP gaps; (2) a nonlinear relationship between data flow and TFP gaps, suggesting an optimal range for its maximum impact. The study concludes that an integrated framework optimizing both data governance and collaborative innovation ecosystems can foster innovation diffusion and support productivity-based competition. These findings provide valuable insights for innovation policy formulation and strategic decision-making in the digital economy. Full article

Background: Language barriers remain a major obstacle to equitable healthcare access for immigrants and refugees across Europe. Greece, as both a transit and host country, faces persistent challenges in providing linguistically and culturally appropriate care. Methods: This study presents a narrative literature review synthesizing international, European, and Greek evidence on the effects of limited language proficiency, professional interpretation, and intercultural mediation on healthcare access, patient safety, satisfaction, and clinical outcomes. Peer-reviewed studies and selected grey literature were identified through searches of PubMed, Scopus, Web of Science, and CINAHL. Results: The evidence consistently demonstrates that the absence of professional interpretation is associated with substantially higher rates of clinically significant communication errors, longer hospital stays, increased readmissions, and higher healthcare costs. In contrast, the use of trained medical interpreters and intercultural mediators improves comprehension, shared decision-making, patient satisfaction, and clinical outcomes. Comparative European data from Italy, Spain, Germany, and Sweden show that institutionalized interpretation systems outperform Greece’s fragmented, NGO-dependent approach. Greek studies further reveal that limited proficiency in Greek is associated with reduced service utilization, longer waiting times, and lower patient satisfaction. Conclusions: This narrative review highlights the urgent need for Greece to adopt a coordinated, professionally staffed interpretation and intercultural mediation framework. Strengthening linguistic support within the healthcare system is essential for improving patient safety, equity, efficiency, and the integration of migrant and refugee populations. Full article