Search Results (15,895)

Conventional melanoma is exceedingly rare in the pediatric population, particularly among prepubescent children, and its diagnosis and management necessitate a multidisciplinary approach. The objective of this present report is to delineate the diagnostic pathway and therapeutic management of a 4-year-old girl with conventional melanoma, with particular focus on the molecular context. A pigmented lesion located on the auricle was surgically excised, and subsequent histopathological and immunohistochemical analyses confirmed the diagnosis of malignant melanoma (pT3b). Radiologic investigations revealed no evidence of metastatic disease, and comprehensive genetic testing utilizing next-generation sequencing (NGS) identified no pathogenic variants in the germline genes examined, nor in the BRAF, NRAS, KRAS, and TP53 genes within the excised lesion. The patient remains in good general health. This case report adds to the limited body of literature on melanoma in pediatric patients and underscores the importance of thorough diagnostic evaluation in this age group. Full article

Coal serves as the primary energy source for China, with production anticipated to reach 4.76 billion tons in 2024. However, the mining process generates a significant amount of gangue, with approximately 800 million tons produced in 2023 alone. Currently, China faces substantial gangue stockpiles, characterized by a low comprehensive utilization rate that fails to meet the country’s ecological and environmental protection requirements. The environmental challenges posed by the treatment and disposal of gangue are becoming increasingly severe. This review employs bibliometric analysis and theoretical perspectives to examine the latest advancements in gangue utilization, specifically focusing on the application of computational chemistry to elucidate the structural features and interaction mechanisms of coal gangue, and to collate how these insights have been leveraged in the literature to inform its potential utilization routes. The aim is to promote the effective resource utilization of this material, and key topics discussed include evaluating the risks of spontaneous combustion associated with gangue, understanding the mechanisms governing heavy metal migration, and modifying coal byproducts to enhance both economic viability and environmental sustainability. The case studies presented in this article offer valuable insights into the gangue conversion process, contributing to the development of more efficient and eco-friendly methods. By proposing a theoretical framework, this review will support ongoing initiatives aimed at the sustainable management and utilization of coal gangue, emphasizing the critical need for continued research and development in this vital area. This review uniquely combines bibliometric analysis with computational chemistry to identify new trends and gaps in coal waste utilization, providing a roadmap for future research. Full article

Understanding the environmental drivers of radial growth in the Pinus massoniana (lamb.) is essential for improving forest productivity and carbon sequestration in subtropical ecosystems. This study used the basal area increment (BAI) as an indicator of radial growth to investigate the main factors affecting the radial growth rate of P. massoniana and the changes in BAI with these factors. A total of 58 high quality tree ring series were analyzed. Six common methods were used to comprehensively analyze the importance of nine factor variables on the BAI, including tree age, competition index, average temperature, and so on. Generalized additive models (GAMs) were developed to explore the nonlinear relationships between each selected variable and the BAI. The results revealed the following: (1) Age and Competition Index was identified as the primary driving force; (2) BAI increased with Age when tree age was below 69 years; (3) from the overall trend, the BAI of P. massoniana decreased with the increase in the Competition Index. These findings provide a scientific basis for developing management plans for P. massoniana forests. Full article

This article aims to explore and analyze current issues and features of environmental protection in managing local tourism destinations based on the principles of sustainable development through the relevant literature and thus to provide an insight into major environmental measures and activities that should be implemented in practice, emphasizing the importance of environmental sustainability as a key factor in the development and success of local tourist destinations in today’s business environment. Qualitative methods were used, with the literature review based on content analysis by keywords. This particularly affects the business process efficiency and the participation of destination stakeholders and in many cases leads to a low level of environmentally sustainable destination practices. In addition to this theoretical approach, this study also has direct managerial implications for destination environmental business operations. An attractive and well-preserved environment is the primary factor of tourism and local tourism destination development and its success, as well as an integrated part of the tourism product. This study addresses a critical gap in the existing literature on environmental sustainability at local destinations, where prior work has often overlooked the integration of actionable, practice-oriented frameworks tailored for both researchers and practitioners. While theoretical insights into sustainable practices abound, there remains a scarcity of holistic analyses that bridge scholarly understanding with implementable strategies for on-the-ground application. To fill this void, our research provides a comprehensive overview and systematic analysis of current practices, with targeted emphasis on co-developing scalable frameworks for improving environmentally sustainable practices at local destinations. Full article

Efficient task offloading for delay-sensitive applications, such as autonomous driving, presents a significant challenge in multi-hop Vehicular Edge Computing (VEC) networks, primarily due to high vehicle mobility, dynamic network topologies, and complex end-to-end congestion problems. To address these issues, this paper proposes a graph attention-based reinforcement learning algorithm, named GAPO. The algorithm models the dynamic VEC network as an attributed graph and utilizes a graph neural network (GNN) to learn a network state representation that captures the global topological structure and node contextual information. Building on this foundation, an attention-based Actor–Critic framework makes joint offloading decisions by intelligently selecting the optimal destination and collaboratively determining the ratios for offloading and resource allocation. A multi-objective reward function, designed to minimize task latency and to alleviate link congestion, guides the entire learning process. Comprehensive simulation experiments and ablation studies show that, compared to traditional heuristic algorithms and standard deep reinforcement learning methods, GAPO significantly reduces average task completion latency and substantially decreases backbone link congestion. In conclusion, by deeply integrating the state-aware capabilities of GNNs with the decision-making abilities of DRL, GAPO provides an efficient, adaptive, and congestion-aware solution to the resource management problems in dynamic VEC environments. Full article

The Lidia cattle breed is featured in several traditional popular bullfighting festivals throughout Spain, including the “Toro de Cuerda” event, in which the animals are subjected to intense physical exercise. However, the physiological impact and welfare implications of these activities remain poorly characterized. This study aimed to evaluate the stress response and muscle damage in Lidia breed bulls during roping bull celebrations through comprehensive blood analysis. Blood samples were collected from 53 adult male Lidia bulls before and after a standardized 45 min continuous running exercise during traditional roping bull events in four Spanish autonomous regions. Hematological parameters, muscle enzymes (creatine kinase, lactate dehydrogenase, lactate), and stress hormones (cortisol and ACTH) were analyzed. Significant increases (p < 0.05) were observed in leukocytes, lymphocytes, monocytes, eosinophils, neutrophils, erythrocytes, hematocrit, hemoglobin, and post-exercise platelets. Muscle enzymes showed marked elevations, with creatine kinase increasing up to 10-fold above baseline values. Stress hormones, cortisol and ACTH, also demonstrated significant increases. Despite the magnitude of these changes, all parameters remained within established reference ranges for the bovine species. This study provides the first physiological assessment of Lidia cattle during popular bullfighting celebrations, establishing baseline data for evidence-based welfare evaluation and management protocols. Full article

Smart safety helmets equipped with vision systems are emerging as powerful tools for industrial infrastructure inspection. This paper presents a comprehensive state-of-the-art review of such VSLAM-enabled (Visual Simultaneous Localization and Mapping) helmets. We surveyed the evolution from basic helmet cameras to intelligent, sensor-fused inspection platforms, highlighting how modern helmets leverage real-time visual SLAM algorithms to map environments and assist inspectors. A systematic literature search was conducted targeting high-impact journals, patents, and industry reports. We classify helmet-integrated camera systems into monocular, stereo, and omnidirectional types and compare their capabilities for infrastructure inspection. We examine core VSLAM algorithms (feature-based, direct, hybrid, and deep-learning-enhanced) and discuss their adaptation to wearable platforms. Multi-sensor fusion approaches integrating inertial, LiDAR, and GNSS data are reviewed, along with edge/cloud processing architectures enabling real-time performance. This paper compiles numerous industrial use cases, from bridges and tunnels to plants and power facilities, demonstrating significant improvements in inspection efficiency, data quality, and worker safety. Key challenges are analyzed, including technical hurdles (battery life, processing limits, and harsh environments), human factors (ergonomics, training, and cognitive load), and regulatory issues (safety certification and data privacy). We also identify emerging trends, such as semantic SLAM, AI-driven defect recognition, hardware miniaturization, and collaborative multi-helmet systems. This review finds that VSLAM-equipped smart helmets offer a transformative approach to infrastructure inspection, enabling real-time mapping, augmented awareness, and safer workflows. We conclude by highlighting current research gaps, notably in standardizing systems and integrating with asset management, and provide recommendations for industry adoption and future research directions. Full article

Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep or heterogeneous arrhythmogenic substrates. Cardiac imaging, especially when multimodal and integrated with mapping systems, has emerged as a critical adjunct to enhance procedural efficacy, safety, and individualized strategy. This comprehensive review explores the evolving role of various imaging modalities, including echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), and intracardiac echocardiography (ICE), in the preprocedural and intraprocedural phases of VT ablation. We highlight their respective strengths in substrate identification, anatomical delineation, and real-time guidance. While limitations persist, including costs, availability, artifacts in device carriers, and lack of standardization, future advances are likely to redefine procedural workflows. Full article

The increasing depletion of fossil fuels and their environmental impact have led to the development of fuel cell hybrid electric vehicles. By combining fuel cells with batteries, these vehicles offer greater efficiency and zero emissions. However, their energy management remains a challenge requiring advanced strategies. This paper presents a comparative study of two developed energy management strategies: a deterministic rule-based approach and a fuzzy logic approach. The proposed system consists of a proton exchange membrane fuel cell (PEMFC) as the primary energy source and a lithium-ion battery as the secondary source. A comprehensive model of the hybrid powertrain is developed to evaluate energy distribution and system behaviour. The control system includes a model predictive control (MPC) method for fuel cell current regulation and a PI controller to maintain DC bus voltage stability. The proposed strategies are evaluated under standard driving cycles (UDDS and NEDC) using a simulation in MATLAB/Simulink. Key performance indicators such as fuel efficiency, hydrogen consumption, battery state-of-charge, and voltage stability are examined to assess the effectiveness of each approach. Simulation results demonstrate that the deterministic strategy offers a structured and computationally efficient solution, while the fuzzy logic approach provides greater adaptability to dynamic driving conditions, leading to improved overall energy efficiency. These findings highlight the critical role of advanced control strategies in improving FCHEV performance and offer valuable insights for future developments in hybrid-vehicle energy management. Full article

This study examines the factors influencing the adoption of enterprise resource planning (ERP) systems within Romanian organizations. The objective is to develop a comprehensive framework for ERP adoption decisions, thereby advancing the field of knowledge and offering managerial insights. To accomplish this research goal, a questionnaire is envisioned, employing various research hypotheses, and distributed to a representative sample. Quantitative econometric regression analysis is employed, considering potential factors such as user training and education, competitive pressures, user involvement and participation, decentralized ERP features, top management support, data quality, the quality of the ERP system, cost and budget considerations, and business process reengineering. Of the 12 factors analyzed, 9 were found to be relevant in terms of influence on the decision to adopt ERP systems, in the context of the Romanian market. The other three factors were found to be irrelevant, thus obtaining results partially different from other areas of the world. By validating the hypotheses and answering the research questions, this work addresses a research gap regarding the lack of a comprehensive understanding of the influencing factors that shape the adoption process of ERP systems in Romania. Full article

The classical V-Model has served as the foundational framework for aerospace systems engineering, but its scope terminates upon aircraft certification, creating a significant gap in addressing reliability degradation during operational service. This study introduces the W-model framework—a comprehensive lifecycle management approach that extends the V-Model to systematically integrate reliability-centered component modifications with established aerospace development practices. The W-model incorporates a structured six-phase reliability-centered modification methodology that transforms operational data into certified design improvements through systematic reliability monitoring, candidate selection, design reviews, development, and certification processes. A detailed case study on the aviation pneumatic bypass valve demonstrates the methodology. Application of the W-model resulted in a 36% improvement in the mean time between failures and a significant reduction in unscheduled removals. The W-model represents a paradigm shift from reactive maintenance strategies to proactive, data-driven reliability enhancement, providing a systematic approach that maintains the rigor and traceability required for commercial aviation while enabling continuous reliability growth throughout the complete aircraft lifecycle. Full article

This comprehensive review examines the role of septoplasty in the pediatric population, emphasizing its therapeutic significance in relieving nasal obstruction and facilitating normal craniofacial growth. Despite the evident advantages of septoplasty, its application in young patients remains a subject of ongoing debate. This issue is primarily characterized by concerns regarding the still-developing immaturity of nasal cartilage, potential intraoperative and postoperative risks, and the current absence of robust data on long-term outcomes following septoplasty. Common complications such as bleeding, septal perforation, saddle nose deformity, and persistent nasal obstruction are reported in the literature; however, many studies lack long-term follow-up data on the incidence of these adverse events and revision rates, which may be higher compared to adult populations, often leading to the need for secondary surgical interventions. Strict inclusion criteria and comprehensive patient selection are paramount to maximize therapeutic success while minimizing complications. Current evidence suggests that appropriately indicated septoplasty can improve airway patency, support optimal facial development, and reduce the risk of secondary sinonasal pathology. There is a significant necessity for additional prospective, large-scale studies to establish standardized therapeutic guidelines and management strategies for this specific population, thereby ensuring effective and evidence-based pediatric otolaryngologic care. Full article

Background: Reverse total shoulder arthroplasty (RTSA) is increasingly used for managing cuff tear arthropathy, osteoarthritis, complex fractures, and revision procedures. As the demand for surgical precision and reproducibility grows, immersive technologies such as virtual reality (VR), augmented reality (AR), and metaverse-based platforms are being explored for surgical training, intraoperative guidance, and rehabilitation. While early data suggest potential benefits, a focused synthesis specific to RTSA is lacking. Methods: This systematic review was conducted in accordance with PRISMA 2020 guidelines. A comprehensive search of PubMed, Scopus, and Cochrane Library databases was performed through 30 May 2025. Eligible studies included those evaluating immersive technologies in the context of RTSA for skill acquisition or intraoperative guidance. Only peer-reviewed articles published in English were included. Data were synthesized narratively due to heterogeneity in study design and outcome metrics. Results: Out of 628 records screened, 21 studies met the inclusion criteria. Five studies evaluated immersive VR for surgical training: four randomized controlled trials and one retrospective case series. VR training improved procedural efficiency and showed non-inferiority to cadaveric training. Sixteen studies investigated intraoperative navigation or AR guidance. Clinical and cadaveric studies consistently reported improved accuracy in glenoid baseplate positioning with reduced angular and linear deviations in postoperative controls as compared to preoperative planning. Conclusions: Immersive technologies show promise in enhancing training, intraoperative accuracy, and procedural consistency in RTSA. VR and AR platforms may support standardized surgical education and precision-based practice, but their broad clinical impact remains limited by small sample sizes, heterogeneous methodologies, and limited long-term outcomes. Further multicenter trials with standardized endpoints and cost-effectiveness analyses are warranted. Postoperative rehabilitation using immersive technologies in RTSA remains underexplored and presents an opportunity for future research. Full article

This study assesses future agricultural drought risk in the Ganjiang River Basin under climate change and land use change. A coupled analysis framework was established using the SWAT hydrological model, the CMIP6 climate models (SSP1-2.6, SSP2-4.5, SSP5-8.5), and the PLUS land use simulation model. Key methods included the Standardized Soil Moisture Index (SSMI), travel time theory for drought event identification and duration analysis, Mann–Kendall trend test, and the Pettitt change-point test to examine soil moisture dynamics from 2027 to 2100. The results indicate that the CMIP6 ensemble performs excellently in temperature simulations, with a correlation coefficient of R² = 0.89 and a root mean square error of RMSE = 1.2 °C, compared to the observational data. The MMM-Best model also performs well in precipitation simulations, with R² = 0.82 and RMSE = 15.3 mm, compared to observational data. Land use changes between 2000 and 2020 showed a decrease in forestland (−3.2%), grassland (−2.8%), and construction land (−1.5%), with an increase in water (4.8%) and unused land (2.7%). Under all emission scenarios, the SSMI values fluctuate with standard deviations of 0.85 (SSP1-2.6), 1.12 (SSP2-4.5), and 1.34 (SSP5-8.5), with the strongest drought intensity observed under SSP5-8.5 (minimum SSMI = −2.8). Drought events exhibited spatial and temporal heterogeneity across scenarios, with drought-affected areas ranging from 25% (SSP1-2.6) to 45% (SSP5-8.5) of the basin. Notably, abrupt changes in soil moisture under SSP5-8.5 occurred earlier (2045–2050) due to intensified land use change, indicating strong human influence on hydrological cycles. This study integrated the CMIP6 climate projections with high-resolution human activity data to advance drought risk assessment methods. It established a framework for assessing agricultural drought risk at the regional scale that comprehensively considers climate and human influences, providing targeted guidance for the formulation of adaptive water resource and land management strategies. Full article

Saproxylic beetles are key bioindicators of forest ecosystem quality and play essential roles in deadwood decomposition and nutrient cycling. However, their populations are increasingly threatened by habitat fragmentation, deadwood removal, and climate-driven environmental changes. For this reason, an integrated sampling method can increase the detection of species with varying ecological traits. We evaluated the effectiveness of integrative sampling methodologies to assess saproxylic beetle diversity within Sila National Park, a Mediterranean forest ecosystem of high conservation value, specifically in two beech forests and four pine forests. The sampling methods tested included Pan Traps (PaTs), Malaise Traps (MTs), Pitfall Traps (PTs), Bait Bottle Traps (BBTs), and Visual Census (VC). All specimens were identified to the species level whenever possible, using specialized dichotomous keys and preserved in the Entomological Collection TB, Unical. Various trap types captured a different number of species: the PaT collected 32 species, followed by the PT with 24, the MT with 16, the VC with 7, and the BBT with 5 species. Interestingly, biodiversity analyses conducted using PAST software version 4.17 revealed that PaTs and MTs recorded the highest biodiversity indices. The GLMM analysis, performed using SPSS software 29.0.1.0, demonstrated that various traps attracted different species with different abundances. By combining multiple trapping techniques, we documented a more comprehensive community composition compared to single-method approaches. Moreover, PaTs, MTs, and PTs recorded 20%, 40%, and 33% of the Near Threatened species, respectively. We report new records for Sila National Park, including the LC species Pteryngium crenulatum (Curculionidae) and the NT species Grynocharis oblonga (Trogossitidae). For the first time in Calabria, the LC species Triplax rufipes (Erotylidae) and the NT species Oxypleurus nodieri (Cerambycidae) and Glischrochilus quadrisignatus (Nitidulidae) were collected. Our results emphasize the importance of method diversity in capturing species with distinct ecological requirements and highlight the relevance of saproxylic beetles as indicators of forest health. These findings support the adoption of multi-method sampling protocols in forest biodiversity monitoring and management programs, especially in biodiversity-rich and structurally heterogeneous landscapes. Full article